{"as_of":"2026-08-09T21:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:481c84a993a932578ee39e5c44aaba1138f3324db96ed33db858bc153cd48987","coverage":[{"denominator":107,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:55:03.237693Z","state":"measured"},{"denominator":101,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":101,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-26T14:26:36.435387Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T06:29:37.631186Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"cited_work":{"arxiv_id":"2507.17342","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.17342","snapshot_observed_at":"2026-07-04T06:29:37.631186Z","title":"DeMo++: Motion Decoupling for Autonomous Driving,","venue":null,"work_id":"fad57734-8bae-4d86-b9eb-5991de215975","year":2025},"citing_paper":{"arxiv_id":"2606.21344","last_updated":"2026-06-19T11:41:52Z","snapshot_observed_at":"2026-08-07T17:36:22.995219Z","submitted_at":"2026-06-19T11:41:52Z","title":"Mind the Noise: Sensitivity of Transformer-based Interaction-Aware Trajectory Prediction Models to Noisy Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-26T14:26:36.435387Z"},"links":{"cited_paper":"/paper/2507.17342","citing_paper":"/paper/2606.21344"},"observation_digest":"sha256:37695848853d9334b3f4a230bde6a058d3cce8d425c9707218aa5faf5d66ea8b","observation_id":"9e25099c-c053-4df6-94be-c30f6880c4f6","resolution":{"observed_at":"2026-07-04T06:29:37.632865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.17342/citation-record","integrity":"/paper/2507.17342/integrity","json":"/paper/2507.17342/citation-record.json","paper":"/paper/2507.17342"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.336080Z","title":"A survey on trajectory-prediction methods for autonomous driving,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.336080Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:208f8983d91129c08f014082fb8b79ccfad69583a2283316f086c83c791730b4","observation_id":"c474ae76-4d1b-42f3-8cab-0f5ab7de3d59","resolution":{"observed_at":"2026-08-06T14:55:02.336080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.346472Z","title":"Scalability in perception for autonomous driving: Waymo open dataset,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.346472Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:5cbcf92b399078c2afe4c18e0f135f7a3d415d0472be4f3f47398a5eb1533535","observation_id":"d52adc44-aee2-4234-8b85-3c854289ef38","resolution":{"observed_at":"2026-08-06T14:55:02.346472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.351816Z","title":"Argoverse 2: Next generation datasets for self-driving perception and forecasting,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.351816Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:f3cdad915398136a9e0c7af31f4aad5efe03f0371cff33bc61150b11746f04b4","observation_id":"fb095283-fc43-4594-94b6-cdb723ab3d5f","resolution":{"observed_at":"2026-08-06T14:55:02.351816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.361898Z","title":"Carla: An open urban driving simulator,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.361898Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:7e22577b1f204b4596c4eb1354bca8364417cc59aa62be918336e87224e00260","observation_id":"22f5afb0-e67e-4e04-a480-57a974675155","resolution":{"observed_at":"2026-08-06T14:55:02.361898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.373319Z","title":"Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.373319Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:b51a8b7228a81f58c0ecd65701f2eca1c5e0fc574cfa2e17a887fbf998830d14","observation_id":"0cec8b34-c544-445f-b1b8-68f31859623c","resolution":{"observed_at":"2026-08-06T14:55:02.373319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.11810","last_updated":"2022-02-04T02:50:02Z","snapshot_observed_at":"2026-08-09T09:38:45.203903Z","submitted_at":"2021-06-22T14:24:55Z","title":"NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.11810","snapshot_observed_at":"2026-08-06T14:55:02.380951Z","title":"nuplan: A closed-loop ml- based planning benchmark for autonomous vehicles,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.380951Z"},"links":{"cited_paper":"/paper/2106.11810","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:7eac03881b979c778b8e697022f7d5f7fdb50842e090dbec9a0b361515b56a84","observation_id":"09551cf8-0a9a-4d49-8a25-6cd80a21d315","resolution":{"observed_at":"2026-08-06T14:55:02.380951Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.390940Z","title":"Vectornet: Encoding hd maps and agent dynamics from vectorized representation,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.390940Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:09dd2770481d40d982599f345e8f62d3fec672b32ffbd6817ddbd805c65aded5","observation_id":"ab79f508-f805-47a3-9ea2-52eb15f1a60d","resolution":{"observed_at":"2026-08-06T14:55:02.390940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.397732Z","title":"Learning lane graph representations for motion forecasting,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.397732Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:288a6df8a6ff78a9d9be48b34e7ef4427a16cd4da813b15956e770e184eabb75","observation_id":"79563bc7-3782-4d44-baa0-ccff841e0d72","resolution":{"observed_at":"2026-08-06T14:55:02.397732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.404326Z","title":"Scene transformer: A unified architecture for predicting future trajectories of multiple agents,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.404326Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:cd7cdd07d37af00333874eab90755df7cb0faae17e085fe120cb1ddb058f906e","observation_id":"aeaa35b2-5933-4386-a4af-b7829d7c43c0","resolution":{"observed_at":"2026-08-06T14:55:02.404326Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.410467Z","title":"Rethinking imitation-based planners for autonomous driving,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.410467Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:645b0786d65c4c453e42459404545ea1dc2159d55d23092b8b9fbc834387c81e","observation_id":"707205a2-75d4-420c-bab4-dbe3301270a1","resolution":{"observed_at":"2026-08-06T14:55:02.410467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.421043Z","title":"Densetnt: End-to-end trajectory prediction from dense goal sets,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.421043Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:60d1a6390a975c1eab62f2ae06ce2d2619b6536c976cbecaa7f81238b6a5040a","observation_id":"e94122ff-fdcc-4f52-a5f7-415cada3d83b","resolution":{"observed_at":"2026-08-06T14:55:02.421043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.427222Z","title":"Eda: Evolving and distinct anchors for multimodal motion prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.427222Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:54f596508a1765c5678782b85c91bc085223663b90a6714810e83b929ef2f8b6","observation_id":"6d4ee5cb-6c45-449e-b976-bdff9a528db1","resolution":{"observed_at":"2026-08-06T14:55:02.427222Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.442709Z","title":"Motion transformer with global intention localization and local movement refinement,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.442709Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:82af214d7524bb0bf0d422fb1b46a1403a63f3dc9c5d2394accbc1b763024ad9","observation_id":"07577687-b4bb-4950-b434-3bf401825d24","resolution":{"observed_at":"2026-08-06T14:55:02.442709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.458339Z","title":"Query-centric trajectory prediction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.458339Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:dd5bda4fe34bc4016cba448559d1f5f52e6fa51ccfb1fe2aec0b5ecfc8ee20bc","observation_id":"96638ca8-a8c0-4e2e-9bed-c8e4196bbdb6","resolution":{"observed_at":"2026-08-06T14:55:02.458339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.468695Z","title":"Diffusiondrive: Truncated diffusion model for end-to-end autonomous driving,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.468695Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:a84087aad90f1862f3d6e1c3602b18c4c5ce2ef80cedb1342a018ddb02dc86a1","observation_id":"185d5b83-b29b-4ef0-b7f0-1ae381b5795b","resolution":{"observed_at":"2026-08-06T14:55:02.468695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.477579Z","title":"Goalflow: Goal-driven flow matching for multimodal trajectories generation in end-to-end autonomous driving,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.477579Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:87c00d3de5e97beff3175241d4ba08d948f90840ffac86b9a17f52fb700c2d3e","observation_id":"49b13cc5-4c47-42a8-81ab-c534736bdea4","resolution":{"observed_at":"2026-08-06T14:55:02.477579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.486478Z","title":"Diffusion-based planning for au- tonomous driving with flexible guidance,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.486478Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:d59b061bf0a1076f1dd157e5a70e66d3e3c5817fda00c9fa0350095689c15c7d","observation_id":"3d07ae20-21c3-4ab9-a63f-26cd8df1f17f","resolution":{"observed_at":"2026-08-06T14:55:02.486478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.492483Z","title":"Reasoning multi-agent behavioral topology for interactive autonomous driving,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.492483Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:6043214b26e150790e99e89e7b88673b867af71629f09b929e8c91d5393d61f3","observation_id":"418c82a2-41a8-4b55-b048-59419be41cca","resolution":{"observed_at":"2026-08-06T14:55:02.492483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.501832Z","title":"End-to-end object detection with transformers,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.501832Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:7edc6bff1215be8861e3d36b09e3c9cb28312aa99713dc758396f0953f6c5799","observation_id":"4290869c-d985-4d65-a436-d7bc3d01cf8a","resolution":{"observed_at":"2026-08-06T14:55:02.501832Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.508248Z","title":"Dab-detr: Dynamic anchor boxes are better queries for detr,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.508248Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:ca292c9aaad3d9df4690fcb439735e647625168e46cd807e09d5c7659266a80f","observation_id":"2fbb8f8f-edde-41e0-bdb2-4666e3e874ea","resolution":{"observed_at":"2026-08-06T14:55:02.508248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-06T14:55:02.518444Z","title":"Mamba: Linear-time sequence modeling with selective state spaces,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.518444Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:cc38845865724434f0c7b4c4ab9f051ff564da416045e4df80cb7a4bf86d00c9","observation_id":"b3f1317b-7419-47c3-a937-b96a0380af0f","resolution":{"observed_at":"2026-08-06T14:55:02.518444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.538584Z","title":"Demo: Decoupling motion fore- casting into directional intentions and dynamic states,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.538584Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:b29a7ea69cfcd3ed8bf81ff8b89147a31a4d766c233bcc717d8c5e0114c108c6","observation_id":"a345e2c7-93ef-49a5-b4ca-104ecd301ae2","resolution":{"observed_at":"2026-08-06T14:55:02.538584Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.550834Z","title":"Motion forecasting in continuous driving,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.550834Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:e876073444ea7c21d93ef9e25b234611094ada5f84e18e49e41903124a0b7145","observation_id":"a6addd12-4fc9-4d73-9724-ee2d3063627d","resolution":{"observed_at":"2026-08-06T14:55:02.550834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.555613Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.555613Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:ffeecae8bd7d1d7cbb5912155e8feac0f16d032ef8ed99cfaa573efedf344dd8","observation_id":"e91035fb-ceab-415d-ba7c-3468ec23dc2a","resolution":{"observed_at":"2026-08-06T14:55:02.555613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.561431Z","title":"Home: Heatmap output for future motion estimation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.561431Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:31fd4368dddbad5b9bfc5165fc0c205f6512431d376080ab6a61822a0721e9fa","observation_id":"f98b7052-9247-46c4-ad43-00d7ff2a3593","resolution":{"observed_at":"2026-08-06T14:55:02.561431Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.568372Z","title":"Covernet: Multimodal behavior prediction using trajectory sets,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.568372Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:48ee6596bf73e1ba7b48be1eb706f16183d463da677d33ebe40ca9f757ba24d5","observation_id":"8890ade9-e209-473f-bf1f-92c9cc76611a","resolution":{"observed_at":"2026-08-06T14:55:02.568372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.577628Z","title":"Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.577628Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:24c82439acadebe1cb25608b591a258218a6ba7ccc21bca32fdd48c1ba3dd738","observation_id":"d4a65f2f-9a14-442f-9963-da8323701a76","resolution":{"observed_at":"2026-08-06T14:55:02.577628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.588678Z","title":"Tnt: Target-driven trajectory prediction,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.588678Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:2a44e3eb21a9f2eb6f798e00c4507adc4bdb48065847dfb9acfd1a1e627f7a66","observation_id":"70c4ab59-4e38-40b0-bc47-ba60953bfa4e","resolution":{"observed_at":"2026-08-06T14:55:02.588678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.598660Z","title":"Hierarchical vector transformer for multi-agent motion prediction,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.598660Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:8b779c51f8d53474dd634b5732d06b794b8700b9b207f53c901bc1e64bba55d1","observation_id":"8fe38603-85f7-4612-98de-247beb5e03ac","resolution":{"observed_at":"2026-08-06T14:55:02.598660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.586922Z","title":"Multimodal trajectory prediction conditioned on lane-graph traversals,","venue":null,"work_id":"53774b17-ac80-4b37-b222-f384741e3521","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.605847Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:b3c89525a9f501a7475d1b453be6bf28ba67583a39d382a57065017c19a20a5d","observation_id":"9bd77cc6-8629-438c-b08a-d652592fbb99","resolution":{"observed_at":"2026-08-06T14:55:05.593685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.566860Z","title":"Gohome: Graph-oriented heatmap output for future motion estima- tion,","venue":null,"work_id":"2d2cf579-d1ad-4e95-8825-f5dfc189627f","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.610947Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:1ad885aed22e7db9904513c13a4f505dbc50af94a8f383c9684789b525be2521","observation_id":"076b5db5-99cc-418c-a258-da7c0b735fea","resolution":{"observed_at":"2026-08-06T14:55:05.573690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.541781Z","title":"Multi-agent trajectory prediction by combining egocentric and allocentric views,","venue":null,"work_id":"32af94a9-a4e9-40f7-a0f1-2e0099dea3c3","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.618572Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:de5a5bfd11ece50f49a64aede4fa4721fbe4c2c8f2b793ee75d3982a9f321fe9","observation_id":"7a311228-99ad-4545-bc67-cb05116862c2","resolution":{"observed_at":"2026-08-06T14:55:05.547832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.518982Z","title":"Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding,","venue":null,"work_id":"0a860a88-4cb3-4ffb-a4f5-fb6f949598e1","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.627115Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:75516a0462477c78a12abc0ac9b56f7e7fbc2e49fe1ebe7d3e5291ecc9164f3d","observation_id":"cffd8c94-8726-4fed-acf2-eb1fa8d4875b","resolution":{"observed_at":"2026-08-06T14:55:05.524782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.496534Z","title":"Fjmp: Factor- ized joint multi-agent motion prediction over learned directed acyclic interaction graphs,","venue":null,"work_id":"567d4be9-9fa2-475f-8c10-d16ebb7a0b2e","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.632659Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:5b65dae677d8f272fc25c285128fd0569d7d97ccabb94d0154edb35758d494cc","observation_id":"ad3c700f-28c3-4136-838b-151d5e431270","resolution":{"observed_at":"2026-08-06T14:55:05.504149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.475287Z","title":"Lanercnn: Distributed representations for graph-centric motion forecasting,","venue":null,"work_id":"06690691-09c0-469b-b57b-5c2db6a0db1d","year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.640364Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:3bcfe5f3c5370a77a08010d73b032c65cb2e091a6092cce420809be4171bd3ff","observation_id":"aa61d12b-759a-405a-b998-ef0a52f2df60","resolution":{"observed_at":"2026-08-06T14:55:05.480708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.451054Z","title":"Trajectory prediction with graph-based dual-scale context fusion,","venue":null,"work_id":"579d408d-86f5-4d8b-8e9a-1cb7626299ae","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.652407Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:45625dd789e519dcea9d1500c8c77b8f4ec8f7bf6c7bec0e183bf1e82df0cf07","observation_id":"3404409f-594b-4ff0-b7ad-e4c4fadd743e","resolution":{"observed_at":"2026-08-06T14:55:05.459843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.424111Z","title":"Multimodal motion prediction with stacked transformers,","venue":null,"work_id":"031643f8-488b-4142-835b-ef9830c9ca1a","year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.660692Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:2d99785903637aaad46654f0774ef29bbafa3ee040179885f3fe97518cb2e847","observation_id":"bd1addc5-cd0f-4878-873e-4db874cfdfc5","resolution":{"observed_at":"2026-08-06T14:55:05.431733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.394177Z","title":"Wayformer: Motion forecasting via simple & efficient attention networks,","venue":null,"work_id":"edbe004b-6cea-4a65-b703-0ff2aa3e7bd6","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.670656Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:10bbd100a71ddd7a9596dab3bc68d5fa66d95752a6e6af7ab3c3566d90cd35f0","observation_id":"2779e402-ae53-413b-a813-07ef31286432","resolution":{"observed_at":"2026-08-06T14:55:05.408940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.367344Z","title":"Real-time motion prediction via heterogeneous polyline transformer with relative pose encoding,","venue":null,"work_id":"143b41a1-da49-401c-9951-7ee5b255702f","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.678494Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:20c66358df0ba2ac3e009e40dbc75fde9ef7266add52b7e49c403755ae3fa3d7","observation_id":"beaa5a5d-600c-468c-83d5-296051c02910","resolution":{"observed_at":"2026-08-06T14:55:05.377025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.691596Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.691596Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:dfa6cdd345e5ed3f7d316c9408d29b31edf0bc79de343a31856620f434515a46","observation_id":"e4a0eba0-f6ca-46f3-be9f-346e9f918ede","resolution":{"observed_at":"2026-08-06T14:55:02.691596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.303497Z","title":"Traj-mae: Masked autoencoders for trajectory prediction,","venue":null,"work_id":"13835cb4-dbf7-4b08-82dc-443cac0d4577","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.700029Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:cc8dd6845f7b1bfd993ba8aa4f9177fc9c22d23a6ee76799eaf2ee1d0fefa92a","observation_id":"2ef25a1d-7080-416a-9422-e2e2b0967805","resolution":{"observed_at":"2026-08-06T14:55:05.310354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.279984Z","title":"Forecast-mae: Self-supervised pre- training for motion forecasting with masked autoencoders,","venue":null,"work_id":"fbbdd579-2131-4042-9bcb-a35ffaa16a53","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.705873Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:efdce05b65bd41ba76eef51321850ccb039728e0a036f34ef0925b704cd06836","observation_id":"58eb2aab-5b56-4920-a4d0-c7335a76f675","resolution":{"observed_at":"2026-08-06T14:55:05.284901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.250504Z","title":"Sept: Towards efficient scene representation learning for motion prediction,","venue":null,"work_id":"5b45aa38-793b-4052-b667-758764ed3659","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.711442Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:fca64c1dea38f3fecb91048c6d9e4b8f7b9453b7492f0e642ca72c0884b1b534","observation_id":"c87b7f1c-f48a-403f-9a77-15796f155326","resolution":{"observed_at":"2026-08-06T14:55:05.257226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.210325Z","title":"T4p: Test- time training of trajectory prediction via masked autoencoder and actor- specific token memory,","venue":null,"work_id":"1d8ee7bb-1f82-40b4-bc7a-ee981caa8aa5","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.718517Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:78bc9c55ef06f76f9d4dec76a01db098ff3591abe47531949aee1aae68eaa2f7","observation_id":"7551a7ea-82cd-4d93-8f9f-510fd627353b","resolution":{"observed_at":"2026-08-06T14:55:05.226806Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.183016Z","title":"Hpnet: Dynamic trajectory forecasting with historical prediction attention,","venue":null,"work_id":"a825f30d-ac64-48c8-8dda-ef9001946453","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.726554Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:a43d152c2e67e37a6dba600ffd3ae7825a545baebad2e0afe25047f3b5ae08c6","observation_id":"308442a3-6bc8-4a2c-a353-26828b3a27a2","resolution":{"observed_at":"2026-08-06T14:55:05.191465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.150587Z","title":"Trajeglish: Learning the lan- guage of driving scenarios,","venue":null,"work_id":"8475fbc0-efc7-4f84-a369-4e36f5c268e1","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.733734Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:0c7963467b09ace8fa5a8c034f8ea9d75191451d98909e910deedff124cd3c45","observation_id":"fa86b887-920c-4fcc-b520-d27a711d63fc","resolution":{"observed_at":"2026-08-06T14:55:05.157886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.120499Z","title":"Motionlm: Multi-agent motion forecasting as language modeling,","venue":null,"work_id":"96b3830a-68e8-4402-a501-11b7cb3e8e2c","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.744368Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:58fb531bbe04b9356e91131845f574518dedb8cab292eb1c9c39aec5675f35b7","observation_id":"54a3c6ed-4f10-4135-95a4-026f879e5341","resolution":{"observed_at":"2026-08-06T14:55:05.126292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.094686Z","title":"R-pred: Two-stage motion prediction via tube-query attention-based trajectory refinement,","venue":null,"work_id":"2b257987-818a-4e8e-8406-1ddf4f8823d2","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.759213Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:954f9ba66ae41d2ea96f4ab02a11ebbb667fc5710b5920356ec704c2481c31df","observation_id":"a58cb99e-98b0-42ad-9be0-7aefcf526f87","resolution":{"observed_at":"2026-08-06T14:55:05.101669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.060690Z","title":"Smartrefine: A scenario-adaptive refinement framework for efficient motion prediction,","venue":null,"work_id":"901c0b8a-5c67-4b5d-9c84-fce97fbe2b05","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.774350Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:102de9258e5a32a16c7b1a761766f853cc903089e01d6c0a899a0cd6e09ece67","observation_id":"e5b5c99a-c6ed-4d2c-8005-2c33dd1e3927","resolution":{"observed_at":"2026-08-06T14:55:05.070708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.031681Z","title":"THOMAS: Trajectory heatmap output with learned multi-agent sam- pling,","venue":null,"work_id":"290f252d-d263-4efd-b02f-c0ae9a34f184","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.784421Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:e825ea47a00a816553c5ddd702c45af55bff0c26eebc8a24affd47ad44ef29fa","observation_id":"c18ce579-9ede-4be3-9d02-acf8a6a1c19a","resolution":{"observed_at":"2026-08-06T14:55:05.037745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:05.003340Z","title":"Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention query- ing,","venue":null,"work_id":"1482e6be-029c-4747-a2db-5ca1e69f52a6","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.795926Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:2401ac7b57fc941268bc4a17fe71c0cc17bdc506419e57f00a40967573a1a9ce","observation_id":"8f36b6a9-d085-44c2-90ff-91f4a43875d6","resolution":{"observed_at":"2026-08-06T14:55:05.015651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.10508","last_updated":"2023-06-18T09:40:40Z","snapshot_observed_at":"2026-08-09T03:39:16.579704Z","submitted_at":"2023-06-18T09:40:40Z","title":"QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.10508","snapshot_observed_at":"2026-08-06T14:55:02.805329Z","title":"Qcnext: A next-generation framework for joint multi-agent trajectory prediction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.805329Z"},"links":{"cited_paper":"/paper/2306.10508","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:d169763295259c4d1d81f192e7822968b5d47040baf599cf29829c232df2d283","observation_id":"9271fba4-fe3f-4bbf-b106-93c43c52a7e3","resolution":{"observed_at":"2026-08-06T14:55:02.805329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.972343Z","title":"Argoverse: 3d tracking and forecasting with rich maps,","venue":null,"work_id":"b2932536-55ad-4516-9dc1-7c0aea4bd4d2","year":2019},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.811369Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:e13f51fc64d66d567e9b81ac3d6c9b9ef0a783eda672020093f43618742957ce","observation_id":"e9852468-241b-46e7-a02e-0f54d29c3bf8","resolution":{"observed_at":"2026-08-06T14:55:04.977343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.948999Z","title":"nuscenes: A multimodal dataset for autonomous driving,","venue":null,"work_id":"da316049-4771-46c3-81dd-27c75e8aaefe","year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.817217Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:67cc7b8ccab00319daf30147a82ae90c65ea6825dcb7a200593710db473f656a","observation_id":"0af33e10-ac6c-48c0-9ccf-e8795f61e4cb","resolution":{"observed_at":"2026-08-06T14:55:04.957127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.825437Z","title":"Congested traffic states in empirical observations and microscopic simulations,","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.825437Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:d959b81ebaac482e5b765cdcd2d5bc3f0a6ff790d5be8586b438ad6ce9deea28","observation_id":"2fed3e0d-68b7-4975-9f4f-901ab3b02933","resolution":{"observed_at":"2026-08-06T14:55:02.825437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:02.834945Z","title":"Parting with misconceptions about learning-based vehicle motion planning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.834945Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:fa6fde610b3108754765f0005a21b78848cf5ae5ad3a9186649abba81c0c3a1b","observation_id":"a9d9d7e8-e7fa-407f-b9d4-921c3ed08d1b","resolution":{"observed_at":"2026-08-06T14:55:02.834945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14327","last_updated":"2024-04-22T16:38:41Z","snapshot_observed_at":"2026-08-08T03:52:57.869549Z","submitted_at":"2024-04-22T16:38:41Z","title":"PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14327","snapshot_observed_at":"2026-08-06T14:55:02.842626Z","title":"Pluto: Pushing the limit of imita- tion learning-based planning for autonomous driving,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.842626Z"},"links":{"cited_paper":"/paper/2404.14327","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:f6a9c9679d8b06d35c8c0e92bc4dcda1a615dbc9896719f735ee08d0c54b26d5","observation_id":"58385734-51fa-4c81-820b-596d9bdad225","resolution":{"observed_at":"2026-08-06T14:55:02.842626Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.895807Z","title":"Planning-oriented autonomous driving,","venue":null,"work_id":"b46c2bed-038c-4bf7-86f4-9040f6031b43","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.852721Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:f1cab7e49506e145906201c549c30b17524ce3bdaaf341ae4c9ed1593d367d38","observation_id":"48c70fee-a7db-4fa7-9d65-99537f152351","resolution":{"observed_at":"2026-08-06T14:55:04.901823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.864152Z","title":"Vad: Vectorized scene representation for efficient autonomous driving,","venue":null,"work_id":"ce722a5f-add4-4ed7-8db1-5f4cb3877809","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.860822Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:80c2331f7381be82bf1ded73750414504a60efdb9706082a2f690c52bc753a1b","observation_id":"c3d2b958-defd-47f6-a7a5-ec460af5b951","resolution":{"observed_at":"2026-08-06T14:55:04.871678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.837167Z","title":"Sparsedrive: End-to-end autonomous driving via sparse scene representation,","venue":null,"work_id":"0aeb3c58-9c67-4503-a6f5-9d3b71d2a7ba","year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.869577Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:aa7bce9fea95219bc753be2d73f8295f503f856fea20137c488f279bfdc78e30","observation_id":"dec5e262-f8d1-4d1c-8994-3137d7363519","resolution":{"observed_at":"2026-08-06T14:55:04.846639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.814807Z","title":"Bridging past and future: End-to-end autonomous driving with historical prediction and plan- ning,","venue":null,"work_id":"12a5ba82-c70d-4550-b303-6d4f1aa33c11","year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.874488Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:50e1b5448b6385329aff0a7b863f31c1e6087e4ffdb19d308b079baa7a0fc68f","observation_id":"79d34542-df47-44ee-a801-68a65bd488ea","resolution":{"observed_at":"2026-08-06T14:55:04.820644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.784106Z","title":"Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,","venue":null,"work_id":"a18aa9ad-7beb-40ba-8611-af98ef81e84b","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.879391Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:f8292e6897f395b4f9579cb9f7e0014dfe7ea8e18a3910e6dbe27514b70a5bf6","observation_id":"598749eb-4b7e-433d-b2dc-9614bc7cb015","resolution":{"observed_at":"2026-08-06T14:55:04.790561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.765198Z","title":"Exploring object- centric temporal modeling for efficient multi-view 3d object detection,","venue":null,"work_id":"2095afe2-353c-42da-9ee8-8de17b199e26","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.885967Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:bce354f17175de46a817d1627bf67a30f90f28fa1472516e1a8732fa74fade4b","observation_id":"6c520e03-5155-45a3-ab4e-7924714a12df","resolution":{"observed_at":"2026-08-06T14:55:04.770639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.741082Z","title":"Trans- fuser: Imitation with transformer-based sensor fusion for autonomous driving,","venue":null,"work_id":"7839ee5d-a226-492b-a8b0-912d973aa9ea","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.892760Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:4bb4849d85196d73226758ea93ad9f90f3173374ad984060d938acba99c1ad14","observation_id":"5fd74ac8-efa7-4c56-8ef1-cb6afd9f10ab","resolution":{"observed_at":"2026-08-06T14:55:04.748934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.715821Z","title":"St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,","venue":null,"work_id":"fc28fb37-efbc-497d-a127-1c988750a88c","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.898948Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:2f3dbd489b172015ebf79bf81c8e63f67199bdf1508be9e2c871d55219a6b81c","observation_id":"1b821a58-2e9f-4165-a472-ac920e2b690b","resolution":{"observed_at":"2026-08-06T14:55:04.721526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.693050Z","title":"Driveadapter: Breaking the coupling barrier of perception and planning in end-to-end autonomous driving,","venue":null,"work_id":"524ae6aa-ae09-4311-930f-3185c9eb793a","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.906648Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:f406503c8e32330b11a16920887216b933bdf555e16fb10b0fe97e3c628b2202","observation_id":"580b485a-aa96-49af-a51a-96eeffcef6c9","resolution":{"observed_at":"2026-08-06T14:55:04.700403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.666514Z","title":"Think twice before driving: Towards scalable decoders for end-to-end autonomous driving,","venue":null,"work_id":"67b999ff-966f-443a-943f-48cd9ad89726","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.914414Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:d2135cdaa6089f77960972c7b488b45ba24ae2e31f5d9f2cbd8507775129d833","observation_id":"a658b00f-4c47-4b70-991c-5f11e87c56fb","resolution":{"observed_at":"2026-08-06T14:55:04.672430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13243","last_updated":"2026-04-17T23:12:55Z","snapshot_observed_at":"2026-08-04T01:21:26.466156Z","submitted_at":"2024-02-20T18:55:09Z","title":"VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13243","snapshot_observed_at":"2026-08-06T14:55:02.927231Z","title":"Vadv2: End-to-end vectorized autonomous driving via probabilistic planning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.927231Z"},"links":{"cited_paper":"/paper/2402.13243","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:9a33beee7df578ffe91f1748187f8debbd54779194c6dab383e6cbc8fffccccf","observation_id":"69d6d64f-95c1-49dd-9c72-fbeeba9cde00","resolution":{"observed_at":"2026-08-06T14:55:02.927231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.641400Z","title":"Enhancing end-to-end autonomous driving with latent world model,","venue":null,"work_id":"bf897e7d-2599-4e8a-bf5d-e665ba424ff9","year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.934572Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:05e1e31e6665b5a42359062fc837bf802f9d8b06d9bb1fcf9d1979326c0d19fc","observation_id":"71677bf1-1568-4507-aecb-04bd12359fcd","resolution":{"observed_at":"2026-08-06T14:55:04.646610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.615466Z","title":"Navigation-guided sparse scene representation for end-to-end autonomous driving,","venue":null,"work_id":"f0ce2531-e68b-4617-8a52-f6ba997e6085","year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.950919Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:e871b65df5e694abbcd222304262f35a7f0c0b2f14c0433905713b036ad002c6","observation_id":"a54cbaf2-d6a5-486d-a0ff-962f461f6221","resolution":{"observed_at":"2026-08-06T14:55:04.623517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.582502Z","title":"Bench2drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving,","venue":null,"work_id":"b151af51-9cdd-456a-8c14-a65cd646d22f","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.957847Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:3cff5eb94b9cfb8343613fe45efc2b61d55e359c1b7502d70a4549071047bf96","observation_id":"bb6299e1-d0cc-4e05-9971-5dc7425cddda","resolution":{"observed_at":"2026-08-06T14:55:04.589166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.555214Z","title":"Drivetransformer: Unified trans- former for scalable end-to-end autonomous driving,","venue":null,"work_id":"515a60ef-c1c6-4003-8490-5e4012fdd5a1","year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.969493Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:d547ce6f4eb829ad8f06f41681d16dc3c15e8dc7b2f10a1361ebf0a18c49e73d","observation_id":"a4ed5742-7537-44f9-8427-eb4f9d63dfe8","resolution":{"observed_at":"2026-08-06T14:55:04.562032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.529494Z","title":"Hungry hungry hippos: Towards language modeling with state space models,","venue":null,"work_id":"c69f7fa8-1bbb-4f47-aac8-50f3c7af7825","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.984133Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:51852b190d457c3ce3a90687ac1626d847180a30e4b8b6293fc4c12875388892","observation_id":"74cf2ab4-337e-4efe-81b0-0e02e4902b59","resolution":{"observed_at":"2026-08-06T14:55:04.540438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.506277Z","title":"Efficiently modeling long sequences with structured state spaces,","venue":null,"work_id":"2882e061-9165-4003-a59a-ff52de20d665","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:02.993479Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:b62cb763065c292f93ba9e9f24ed6b730f2dc2afc7f4b704bf90a4c8b65bc354","observation_id":"fcd31c3e-eb43-410d-9fc6-693f31c81dd5","resolution":{"observed_at":"2026-08-06T14:55:04.515570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.483030Z","title":"Simplified state space layers for sequence modeling,","venue":null,"work_id":"d9f948a7-03f4-44fb-88dd-2a90a4e55a35","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.004363Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:1502207e6fcb7f732d3da9ce6fc69d1c7d7b2c3ce720d967dc0526c371013468","observation_id":"cd14c2f8-0000-404a-b6d5-c65918ead8c7","resolution":{"observed_at":"2026-08-06T14:55:04.490368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00818","last_updated":"2024-03-05T14:31:03Z","snapshot_observed_at":"2026-08-04T17:22:50.607490Z","submitted_at":"2024-02-26T09:21:59Z","title":"DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00818","snapshot_observed_at":"2026-08-06T14:55:03.012691Z","title":"Densemamba: State space models with dense hidden connection for efficient large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.012691Z"},"links":{"cited_paper":"/paper/2403.00818","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:a82df571da53ca9a36bfdafe3e0e7c94619aabdc5c58b6fe8cd9eabb4961b1b8","observation_id":"aca3df03-ee8f-49af-8f0a-c4023f099d45","resolution":{"observed_at":"2026-08-06T14:55:03.012691Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.19887","last_updated":"2024-07-03T14:30:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-03-28T23:55:06Z","title":"Jamba: A Hybrid Transformer-Mamba Language Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.19887","snapshot_observed_at":"2026-08-06T14:55:03.028732Z","title":"Jamba: A hybrid transformer-mamba language model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.028732Z"},"links":{"cited_paper":"/paper/2403.19887","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:cdbeee532e9b1399f5104d22f40ef745d521fa19f8b0a0bec3c6b563ed183404","observation_id":"fd8b479c-8ad8-4922-9211-7a60bc8e3ba7","resolution":{"observed_at":"2026-08-06T14:55:03.028732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.453680Z","title":"Zigma: A dit-style zigzag mamba diffusion model,","venue":null,"work_id":"36dd1dc0-fb55-405e-8573-44c477239670","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.042569Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:b847fadc21c1f2811b9d0555af144caa28708aeb97e61bfa6cd3fcd9bc8ab803","observation_id":"8c593e3b-e3f1-4003-9401-d65905c3e22a","resolution":{"observed_at":"2026-08-06T14:55:04.469170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.412371Z","title":"Videomamba: State space model for efficient video understanding,","venue":null,"work_id":"e0e7e095-9322-4790-a262-f83e600e41e4","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.055470Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:6b2142f2b7b683c1da7840f41e2aef42c7ae4bf09c80a97236663f05913270ce","observation_id":"43efc955-358c-402f-92e4-919ec9a48497","resolution":{"observed_at":"2026-08-06T14:55:04.418955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.391724Z","title":"Motion mamba: Efficient and long sequence motion generation with hierarchical and bidirectional selective ssm,","venue":null,"work_id":"8a152160-e7f6-4958-a238-8fd6114d21ad","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.061431Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:56ea5849ecf34022c71a711d29c5d63ebf86a3f98ca93bd35c0de6424a147268","observation_id":"ccd59e8c-66bd-416e-bfce-a931cc00846c","resolution":{"observed_at":"2026-08-06T14:55:04.398272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.367439Z","title":"Vision mamba: Efficient visual representation learning with bidirectional state space model,","venue":null,"work_id":"fdbfbacc-1e2a-4205-84e8-5de2497d7258","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.073695Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:7b15e39ec17f1d1ccd6578f56203f26dee035d40a5916f66a60cbafd2e59d122","observation_id":"c1e80e13-ebeb-44d8-b117-be04e8c83bed","resolution":{"observed_at":"2026-08-06T14:55:04.374895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.336510Z","title":"End-to-end driving with online trajectory evaluation via bev world model,","venue":null,"work_id":"fff292f7-56d8-4aa2-9afa-dd3663fd835d","year":2025},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.094821Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:80d4463572e902912fd8b15c7d524de0771e075823c8169fe724b4a679267b0a","observation_id":"c69ebbb1-54d1-45d6-863a-b79d7f6bf03c","resolution":{"observed_at":"2026-08-06T14:55:04.345651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06978","last_updated":"2024-08-30T03:37:36Z","snapshot_observed_at":"2026-07-06T18:28:42.314877Z","submitted_at":"2024-06-11T06:18:26Z","title":"Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06978","snapshot_observed_at":"2026-08-06T14:55:03.108602Z","title":"Hydra-mdp: End-to-end multimodal planning with multi- target hydra-distillation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.108602Z"},"links":{"cited_paper":"/paper/2406.06978","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:f79994b055b5b740d3d257f07a70458574472ac417c4f34086bca062109d7053","observation_id":"f1b3170a-933c-4e02-9606-c9192d503368","resolution":{"observed_at":"2026-08-06T14:55:03.108602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.310629Z","title":"Deformable detr: Deformable transformers for end-to-end object detection,","venue":null,"work_id":"a3f21b06-8a35-4ab1-9c81-60a6cf6542a3","year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.121214Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:1c7ea153d02e6809e34e0c55336d923d4518e65b37f3a7b44029b16b2f60d350","observation_id":"6d1c3b5b-c771-405e-8b88-5fb65c7b26fe","resolution":{"observed_at":"2026-08-06T14:55:04.320243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.251489Z","title":"Leveraging future relationship reasoning for vehicle trajectory prediction,","venue":null,"work_id":"b2bfa537-bfd7-4b27-9875-f10f5ff9fcfe","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.128251Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:ae76f74919dfc20aa17e3df4674560936990058900eb0dfa2210eb1418df72b7","observation_id":"ae1c7e15-8f57-4c94-a82c-ac5c0b052f52","resolution":{"observed_at":"2026-08-06T14:55:04.272674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.212520Z","title":"Simpl: A simple and efficient multi-agent motion prediction baseline for autonomous driving,","venue":null,"work_id":"e8891169-d6a2-45cf-826c-521571cb9bdd","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.139055Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:8631defe6846a90f74933772a60326760909a8a473a605afb81ac5ee02cb893f","observation_id":"75233508-c274-4bef-b881-c12b6004521d","resolution":{"observed_at":"2026-08-06T14:55:04.223493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.184599Z","title":"Gorela: Go relative for viewpoint-invariant motion forecasting,","venue":null,"work_id":"249bff13-f26f-4fd5-b813-21108e9b9e4f","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.144439Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:91dd02aef626c1494dd0fe2b2f69f8637e6cd376e713320600c6f242466adaeb","observation_id":"430a2e74-4f8c-4167-ba43-951867f9b5cc","resolution":{"observed_at":"2026-08-06T14:55:04.193274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.159007Z","title":"Ganet: Goal area network for motion forecast- ing,","venue":null,"work_id":"87bd8525-9c47-4ad2-a650-90144a02691a","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.149425Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:20a0893db91daf563715a88341f62ccca8abf78dd74ed3f71e60830a89cd1a0a","observation_id":"4941ff46-1abf-43cb-b9b3-a486e676f43d","resolution":{"observed_at":"2026-08-06T14:55:04.169817Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.129682Z","title":"Prophnet: Efficient agent- centric motion forecasting with anchor-informed proposals,","venue":null,"work_id":"433b04d7-b7b7-4259-bc6a-5a9d4c7c7b1b","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.159162Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:a1004a64bfa6d2966dd2085ad9cacca7f86bfd06825e0ff6d6c942014f904637","observation_id":"f0af3fc2-2803-45e7-aaaa-9ba871ffa38d","resolution":{"observed_at":"2026-08-06T14:55:04.137720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.098694Z","title":"Cadet: a causal dis- entanglement approach for robust trajectory prediction in autonomous driving,","venue":null,"work_id":"eceb9b4c-503b-42a0-ab6c-c1427e7dd441","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.165446Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:4246e136092c2216973678aede35a0fff336fb7a940a43977bc1b51fb0e25fb0","observation_id":"359c90af-463f-4be3-8cb3-8e120fd506e8","resolution":{"observed_at":"2026-08-06T14:55:04.104657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.074696Z","title":"Trajec- tron++: Dynamically-feasible trajectory forecasting with heterogeneous data,","venue":null,"work_id":"7c2395d6-c583-47a5-a06b-b24b41f85000","year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.170572Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:a166d57455e7d26498c7f40882678b28d923430e43ecc05de103938dd506af8d","observation_id":"2871e256-def9-4966-aba8-9041c91d51ff","resolution":{"observed_at":"2026-08-06T14:55:04.082447Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.050874Z","title":"Lapred: Lane-aware prediction of multi- modal future trajectories of dynamic agents,","venue":null,"work_id":"01404653-11b6-40c3-b5da-2a433e64d8de","year":2021},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.177156Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:32c192206f78c86080c83136b95358bb286d055cf95674fba9c6e5975bf69545","observation_id":"d98a24f7-07cc-4705-9d20-5f1e0579b9bb","resolution":{"observed_at":"2026-08-06T14:55:04.058920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.00735","last_updated":"2021-04-29T17:35:21Z","snapshot_observed_at":"2026-08-09T07:33:50.314251Z","submitted_at":"2020-01-03T06:12:26Z","title":"Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans","version":2},"cited_work":{"arxiv_id":"2001.00735","doi":null,"metadata_source":"pith","pith_arxiv_id":"2001.00735","snapshot_observed_at":"2026-08-06T14:55:03.478451Z","title":"Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans","venue":"cs.CV","work_id":"c147e10a-a042-429e-9327-18aa022f88c9","year":2020},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.184671Z"},"links":{"cited_paper":"/paper/2001.00735","citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:9550b9a6e5eeeb61e6e25d528439a3d79ed7ca6ebff8387b88fdd7a0ba56a32c","observation_id":"c9db8663-776e-4d26-a35f-ef8908f73f56","resolution":{"observed_at":"2026-08-06T14:55:03.489981Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:04.023558Z","title":"Context-aware scene prediction network (caspnet),","venue":null,"work_id":"cf821fde-68a1-4d90-b621-3c8803aff9d1","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.194758Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:3593012334d1e282ddd465d35db9b6603f49110cc99bd72074715d5cff3eec11","observation_id":"31911290-1684-4edf-86db-32e41e319f55","resolution":{"observed_at":"2026-08-06T14:55:04.030519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:03.993138Z","title":"Latent variable sequential set transformers for joint multi-agent motion prediction,","venue":null,"work_id":"79252a25-a840-40c0-b19c-b3d06bc27fea","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.202156Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:6977ce868e78bc92673082e0b32dc82814c31dc4c8197d45a3d477cb2ddd000d","observation_id":"0ebd50ba-663b-4336-bfc0-9eb7ff6c03be","resolution":{"observed_at":"2026-08-06T14:55:03.999744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:03.964045Z","title":"Laformer: Trajectory prediction for autonomous driving with lane-aware scene constraints,","venue":null,"work_id":"98cd9b7a-fa38-492f-8df5-088cfc6ab555","year":2024},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.209273Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:8dd5b370bc35938ef370afbc845570c68a750ca2b2760f34fc16995aec2bfbe8","observation_id":"0f26fe46-eecd-42cb-8089-e7b57ff1925d","resolution":{"observed_at":"2026-08-06T14:55:03.971575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:03.939929Z","title":"Gameformer: Game-theoretic modeling and learning of transformer-based interactive prediction and planning for autonomous driving,","venue":null,"work_id":"abcd74dc-e617-4a15-b645-f49a3d478ca9","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.213471Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:074f54892ac4be7e4112e4da5af552050d6f0125f40dcaae19acc23d888f620b","observation_id":"f018add9-7990-4a5c-87a8-0ea341e13218","resolution":{"observed_at":"2026-08-06T14:55:03.947953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:03.906737Z","title":"Urban driver: Learning to drive from real-world demonstrations using policy gradients,","venue":null,"work_id":"599e9240-6e62-465a-86d7-a5c213a2b30d","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.222478Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:0008b84fdc71773cf7b5b650e92e5d6165aec6bec5b3c1bccc854360c23e0f00","observation_id":"00f06584-cf4d-4800-bb30-3517d415c9fb","resolution":{"observed_at":"2026-08-06T14:55:03.916321Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:03.876562Z","title":"Plant: Explainable planning transformers via object-level representations,","venue":null,"work_id":"885cdb95-df39-471b-aa61-271b012a992c","year":2022},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.231147Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:3c36a289a4c65a14a95af0322153f5c55961b2cef0acfdd49f601cac4f99d98e","observation_id":"ceb285d5-dfb5-4d04-b98c-53bbeae13af5","resolution":{"observed_at":"2026-08-06T14:55:03.885010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:55:03.845513Z","title":"From prediction to planning with goal conditioned lane graph traversals,","venue":null,"work_id":"95e530da-bf5c-47d9-ba0f-16110d1a62ad","year":2023},"citing_paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-06T14:55:03.237693Z"},"links":{"citing_paper":"/paper/2507.17342"},"observation_digest":"sha256:7f920ece957059ba791a5be1593eb07e026549e60b28ec8bfb128eef500872ca","observation_id":"3508f69e-c7b9-4d25-839d-d6ba38490001","resolution":{"observed_at":"2026-08-06T14:55:03.854622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.17342","last_updated":"2025-08-06T04:07:17Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T14:47:48.892761Z","submitted_at":"2025-07-23T09:11:25Z","title":"DeMo++: Motion Decoupling for Autonomous Driving"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":38,"verified_exact":1,"verified_fuzzy":61},"total_outbound_references":107},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 100 of 107 outbound references and 1 inbound Pith citation observation for arXiv:2507.17342."}