{"as_of":"2026-08-18T00:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:19fc1ed80bb90a0e60de6cc3254b5da03ec0477ab7ecca3d549ce9d8e331e28b","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T22:55:46.049173Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.06181/citation-record","integrity":"/paper/2508.06181/integrity","json":"/paper/2508.06181/citation-record.json","paper":"/paper/2508.06181"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:55:41.568083Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:41.568083Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:33800152c7037ae690a076606274b5a9624b77971a50bf75f393b016eca253fa","observation_id":"a6068420-ffd3-4dd7-bdb4-f1461e717158","resolution":{"observed_at":"2026-08-05T22:55:41.568083Z","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":"2026-08-05T22:55:48.268567Z","title":"Kober, J","venue":null,"work_id":"ca6bfcf7-1725-458a-91c7-8308a40f0dc3","year":2013},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:41.650058Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:92a92bbef1de2285a743709b352def3526869e4edd915647c26794163d80b8f0","observation_id":"661bc7c3-4a21-4983-a3b8-6c027310e596","resolution":{"observed_at":"2026-08-05T22:55:48.272913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.254826Z","title":"Jiang, T","venue":null,"work_id":"70677aa1-3e30-4bfd-aa7e-f506f2ced2db","year":2020},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:41.752105Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:4089cb20cbdd57ce4049caf9498bfde4b52b952fcc2294d49ee43f7c368ca14e","observation_id":"8e27e561-6c41-48d8-9b4a-f0d830770972","resolution":{"observed_at":"2026-08-05T22:55:48.259301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.240477Z","title":"Brunke, M","venue":null,"work_id":"1e1b901f-040a-4d69-99ad-bc3de1191c27","year":2022},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:41.876660Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:cbf6eccc0b4b376dd92265997ec0191770cdd2e8b1011e31bea5f51fdeb72ceb","observation_id":"ed5d9721-cc9e-4ddd-a8d8-7048e8cf7822","resolution":{"observed_at":"2026-08-05T22:55:48.245121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.226872Z","title":"Czechmanowski, J","venue":null,"work_id":"603e73a0-ad47-4528-8938-e314b6942d34","year":2025},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:41.950113Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:7eda29f7c2b2ab0bf717f17c03a16084ad0f5e6aec67ed0aa9ce8a9f08d7c00a","observation_id":"9092ee2c-e2ed-45a8-ab14-0d4b6b38e5de","resolution":{"observed_at":"2026-08-05T22:55:48.231162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.212634Z","title":"Song and D","venue":null,"work_id":"0548cc93-e422-42b3-ad44-aeb5a4dbd371","year":2022},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.049729Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:0d47f6180e0d074734f2953d4d66370e2cdad321e3871889574081b648ade977","observation_id":"32a07977-0029-42dd-bd3a-4b4b38136e30","resolution":{"observed_at":"2026-08-05T22:55:48.217313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10943","last_updated":"2023-10-18T14:32:37Z","snapshot_observed_at":"2026-08-16T14:51:33.815111Z","submitted_at":"2023-10-17T02:40:27Z","title":"Reaching the Limit in Autonomous Racing: Optimal Control versus Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2310.10943","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.10943","snapshot_observed_at":"2026-08-05T22:55:47.735273Z","title":"Reaching the Limit in Autonomous Racing: Optimal Control versus Reinforcement Learning","venue":"cs.RO","work_id":"e5803337-9df3-46f0-922f-4f511a27a012","year":2023},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.155930Z"},"links":{"cited_paper":"/paper/2310.10943","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:6ead6d1e2c7f7f5e64c8926bf21d5b255674ef2e61867734a18a77eae7f3c7d8","observation_id":"347f9a3c-8228-41c4-8391-ca73e7673db9","resolution":{"observed_at":"2026-08-05T22:55:47.739873Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.197311Z","title":"Krinner, A","venue":null,"work_id":"6949fbce-d4ca-435b-a136-df36e5420ff5","year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.261841Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:8756ec71c0a2a9e724c1013682b14b98f434cc75167c297c5a0dfd89d7b4df97","observation_id":"c0eba539-e0ee-4d7b-8a52-e9e0fb2974e8","resolution":{"observed_at":"2026-08-05T22:55:48.201861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.183574Z","title":"Kabzan, L","venue":null,"work_id":"4d0126f8-d2cb-4cc7-bf14-bb2f499e5e02","year":2019},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.367530Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:4e07edf8079f1aeea4331a0bf24f41b9ade77a023a9c443b6b9a06d84ee81fa0","observation_id":"4a84d1af-c8ad-4bff-8241-542ae9bd8dba","resolution":{"observed_at":"2026-08-05T22:55:48.187638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.169543Z","title":"Chrosniak, J","venue":null,"work_id":"561f5016-912f-415a-aa32-7d658bc1da78","year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.472461Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:2231fd8ac95673973023f4a0c871438e99fdd6b89f1c304999c33c52adcf12d4","observation_id":"86f648c6-a750-4581-8618-06a72e2ff176","resolution":{"observed_at":"2026-08-05T22:55:48.174064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.155589Z","title":"Neunert, M","venue":null,"work_id":"336ba600-e2c3-49ae-9f9c-bbe4bdc6d95b","year":2018},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.581408Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:56cc9bbc078b1c83c8a744fc413d59741ce8011de83e3fe918286500980eefec","observation_id":"8db7cfe3-7ced-4b12-a137-0a0bfc914ee9","resolution":{"observed_at":"2026-08-05T22:55:48.159810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.141886Z","title":"Grandia, F","venue":null,"work_id":"0fc3f515-62f7-429d-a46d-03eaf7825d69","year":2019},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.687089Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:21a877697c93365b9181eb2147a1e2351c93eca8279f6e373302d544a4cb094b","observation_id":"5dc6e050-3b33-49bb-b061-1c4c9cec019c","resolution":{"observed_at":"2026-08-05T22:55:48.146162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.128472Z","title":"Hewing, A","venue":null,"work_id":"9e0df5b2-91e0-4f9f-a396-96477b7547c6","year":2018},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.797107Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:374b63132c2398ae2f64e1e66188643509d9b16eb5a4e471b7530b25798570f2","observation_id":"304a02ba-f8e4-4960-9e33-3e73a1306d25","resolution":{"observed_at":"2026-08-05T22:55:48.132527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.05773","last_updated":"2021-03-03T17:12:54Z","snapshot_observed_at":"2026-08-16T18:46:20.411816Z","submitted_at":"2021-02-10T23:18:54Z","title":"Data-Driven MPC for Quadrotors","version":2},"cited_work":{"arxiv_id":"2102.05773","doi":null,"metadata_source":"pith","pith_arxiv_id":"2102.05773","snapshot_observed_at":"2026-08-05T22:55:47.714831Z","title":"Data-Driven MPC for Quadrotors","venue":"cs.RO","work_id":"0f1e31ff-78e1-4e38-862f-1a6f4b9cc11c","year":2021},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:42.939992Z"},"links":{"cited_paper":"/paper/2102.05773","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:c7cee9ae9336e42d13cfb86cf61821f250544d5346d092c7b31247aa29dfbf2f","observation_id":"1fdc5f2f-5c47-4d6a-8ba1-2fc718a116a4","resolution":{"observed_at":"2026-08-05T22:55:47.719647Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.114807Z","title":"Kaufmann, L","venue":null,"work_id":"6d5e8d84-cdb9-4042-ad4b-8ab098ebb004","year":2023},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.092145Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:c1d3c1262b3a652b2298173ec4b2c4e98870ee6b481ef4e44c6ae1e057514c73","observation_id":"b4a465f6-b4f3-44ca-bd3c-da206ed7117c","resolution":{"observed_at":"2026-08-05T22:55:48.118984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.101524Z","title":null,"venue":null,"work_id":"247c8d1c-add5-4844-a817-4532a78acd68","year":2019},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.256731Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:bb4d60b5e61b2cd4fd966be0c7cc0de6da79bd22a19d6277f43778168792c422","observation_id":"c2f97042-0f04-4ee9-af8c-b6ddfdf249ab","resolution":{"observed_at":"2026-08-05T22:55:48.105587Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04821","last_updated":"2022-01-11T16:22:20Z","snapshot_observed_at":"2026-08-16T21:02:34.588735Z","submitted_at":"2021-09-10T12:09:18Z","title":"KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework for Aerial Robots","version":3},"cited_work":{"arxiv_id":"2109.04821","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.04821","snapshot_observed_at":"2026-08-05T22:55:47.694013Z","title":"KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework for Aerial Robots","venue":"cs.RO","work_id":"1dc84271-9e1e-429d-a8df-0fc720b4d5d7","year":2021},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.424684Z"},"links":{"cited_paper":"/paper/2109.04821","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:60154890db1751d7aa84fd52ba8db64f3057b7fe968b211f242102953fca73c4","observation_id":"16993e74-0436-49cd-b28e-5708d26f38e7","resolution":{"observed_at":"2026-08-05T22:55:47.698557Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.07747","last_updated":"2023-07-25T08:19:39Z","snapshot_observed_at":"2026-08-17T05:43:52.449091Z","submitted_at":"2022-03-15T09:38:15Z","title":"Real-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms","version":5},"cited_work":{"arxiv_id":"2203.07747","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.07747","snapshot_observed_at":"2026-08-05T22:55:47.658036Z","title":"Real-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms","venue":"cs.RO","work_id":"bd9b5f99-9d09-4fba-864b-26eba361ac40","year":2022},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.587466Z"},"links":{"cited_paper":"/paper/2203.07747","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:cd4c9901ab132a579773285390c85ed5644aae8d22452ac7c6afae13664ccae9","observation_id":"0da966e5-64ee-49dc-8313-9c8818aaaff6","resolution":{"observed_at":"2026-08-05T22:55:47.677176Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.08567","last_updated":"2019-01-24T18:34:50Z","snapshot_observed_at":"2026-08-14T17:26:19.804577Z","submitted_at":"2019-01-24T18:34:50Z","title":"F1/10: An Open-Source Autonomous Cyber-Physical Platform","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.08567","snapshot_observed_at":"2026-08-05T22:55:43.709704Z","title":"O'Kelly, V","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.709704Z"},"links":{"cited_paper":"/paper/1901.08567","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:42fedc16296840b8bb4d8e51b6a9669db9cf79b3ca61cb7c1ca443b686c36a40","observation_id":"de71cffb-aed4-4c9e-b6ce-9ba2ecaab740","resolution":{"observed_at":"2026-08-05T22:55:43.709704Z","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":"2026-08-05T22:55:48.088571Z","title":"Schwenzer, M","venue":null,"work_id":"6485dc28-1193-4091-a057-dd35bce8d701","year":2021},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.779347Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:d0189eb542504cb8a850005b57342b1ac5e36bac324f69eee1c48abf75e9c2bb","observation_id":"7c8ca2d1-c721-4bd5-870f-c69487dd8b0b","resolution":{"observed_at":"2026-08-05T22:55:48.092446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.075411Z","title":"Williams, P","venue":null,"work_id":"739d24c3-2a2e-4f0f-bbe3-14594860ec09","year":2016},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.853387Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:09921a9ecb5f76e20095db5c1ee88c5a7fc06053ff50854c8ee679868b7ce04e","observation_id":"b78e0655-5c87-43d8-bde1-93ba44a83475","resolution":{"observed_at":"2026-08-05T22:55:48.079811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.061964Z","title":"Williams, N","venue":null,"work_id":"f5659265-6cc0-4676-8418-67bbc47d7bfd","year":2017},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:43.923315Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:cc5eaf1b2822b44295a5c83d51260616030e473ab7def3b08021f5a9b69c2239","observation_id":"d3f5bfbb-7f4b-4445-8218-a78407426e34","resolution":{"observed_at":"2026-08-05T22:55:48.066187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.048117Z","title":"Pinneri, S","venue":null,"work_id":"03b6fe1b-965f-4910-b903-7c49f7973cc7","year":2020},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.057924Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:efb149ecddd19600bb383099c90179e998d90082e6ea4b457220fb3dc646ee7b","observation_id":"47a514e0-6504-41bf-af20-9107595d8a74","resolution":{"observed_at":"2026-08-05T22:55:48.052681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08674","last_updated":"2023-10-12T19:20:32Z","snapshot_observed_at":"2026-08-16T14:52:33.310511Z","submitted_at":"2023-10-12T19:20:32Z","title":"Pay Attention to How You Drive: Safe and Adaptive Model-Based Reinforcement Learning for Off-Road Driving","version":1},"cited_work":{"arxiv_id":"2310.08674","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.08674","snapshot_observed_at":"2026-08-05T22:55:47.347797Z","title":"Pay Attention to How You Drive: Safe and Adaptive Model-Based Reinforcement Learning for Off-Road Driving","venue":"cs.RO","work_id":"26b2b150-20bb-4bc5-9d13-72def4834521","year":2023},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.184469Z"},"links":{"cited_paper":"/paper/2310.08674","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:a0528bebafecedd5252b6fa302f2da6e481d9531de3d3a594d1b7690b8753477","observation_id":"72bac321-ce69-47ec-ac08-a244924b51c2","resolution":{"observed_at":"2026-08-05T22:55:47.480311Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.033060Z","title":"Williams, P","venue":null,"work_id":"f820f4dd-d2c4-4b9b-b10d-b5b52fd619c7","year":2018},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.300206Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:7973a47ed98b651609e0cfde3696dd7f6edb300f348eaed3d8f1dee0e98f4170","observation_id":"19cfa110-0e54-4936-9357-fb4dbd615fe1","resolution":{"observed_at":"2026-08-05T22:55:48.037710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.15783","last_updated":"2024-09-24T06:27:13Z","snapshot_observed_at":"2026-08-16T13:15:59.317536Z","submitted_at":"2024-09-24T06:27:13Z","title":"AnyCar to Anywhere: Learning Universal Dynamics Model for Agile and Adaptive Mobility","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.15783","snapshot_observed_at":"2026-08-05T22:55:44.416337Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.416337Z"},"links":{"cited_paper":"/paper/2409.15783","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:f0de47e57f1a4d1a56a553a3471cd58db49ab18a54aee9d3f94b0aaa4539d545","observation_id":"b382b8aa-0bb6-4513-b4e6-5e2692a0e097","resolution":{"observed_at":"2026-08-05T22:55:44.416337Z","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":"2021.31316","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:55:47.158561Z","title":"Hanover, P","venue":null,"work_id":"bced2102-d16d-435e-a0b0-5c96b9f6963c","year":2022},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.531498Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:565a22ecdb24e8bb49c50f151c063702a77a397a440d909b4603e576cf02d276","observation_id":"ce279009-79f3-48af-afc2-66a222f3769a","resolution":{"observed_at":"2026-08-05T22:55:47.206107Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.018316Z","title":"Salzmann, J","venue":null,"work_id":"d784a1e3-9d0d-4850-b804-d3b542f6b84a","year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.607344Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:9b0a1ae007c9f52235c407c0a4cdfa667691a7598f4f826f94659c347b994ea7","observation_id":"46933098-c61a-4bda-8788-669e481d4fdd","resolution":{"observed_at":"2026-08-05T22:55:48.022391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:48.004211Z","title":"Verschueren, M","venue":null,"work_id":"c8d52e7b-4e45-4c74-9044-4733efa13060","year":2016},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.679310Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:170517a49d380faa1e093d6733672227b60b61e08d68f9bf25bd4dd13d1706c4","observation_id":"ce7dedb4-9a52-481d-8be2-19945c140d18","resolution":{"observed_at":"2026-08-05T22:55:48.008113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.990736Z","title":"Liniger, A","venue":null,"work_id":"858cdd3f-b19c-4c82-aee1-630d4d59b78a","year":2015},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.751918Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:537635ab8c02307bc653ef1b9d380519a114611e393837ee9120e95bc01e5429","observation_id":"d1121e8b-bde0-4056-bfdd-9c7f50a79138","resolution":{"observed_at":"2026-08-05T22:55:47.994781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.976919Z","title":"Hansen, H","venue":null,"work_id":"e79c9fb2-6d03-4113-b8f6-b48917440fb4","year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.832591Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:89abffc820593b424d183d9265ae442a8cd0ad6881b292c3106e615a98e72195","observation_id":"72ae953f-e730-4e40-9e2a-921003b2ae96","resolution":{"observed_at":"2026-08-05T22:55:47.980934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.963346Z","title":"Zhang, S","venue":null,"work_id":"9b9feb29-14a8-417d-9aa0-d0bab3d01faf","year":2019},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.882206Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:80e915c8fc5ad2e7b645d2d5b8fd6ea8bedd55c16f6ee4856067d369b7828a59","observation_id":"48d75324-b425-4878-9b30-086010cd7072","resolution":{"observed_at":"2026-08-05T22:55:47.967340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.949857Z","title":"Zhang, M","venue":null,"work_id":"80c99209-5834-4c48-bc0d-d5ec2eed14f7","year":2019},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:44.980530Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:20d143e0c9fe0131e8993256841551f68128556250401d626774dac3c02c64be","observation_id":"6e6f43c6-223e-4e97-b5ed-e3f71008837b","resolution":{"observed_at":"2026-08-05T22:55:47.954123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.935546Z","title":"Hegde, Z","venue":null,"work_id":"be16ab94-d94a-41d2-8c3d-3c454d48bb1f","year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.015968Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:13b7a068cb89c2a9d4d018ddfbfbf512d48722ea21b09ef5bb355fb6952241c8","observation_id":"76bc1239-db9e-4645-aa8f-a5de8ca0723a","resolution":{"observed_at":"2026-08-05T22:55:47.939681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.921554Z","title":null,"venue":null,"work_id":"f1015d87-134b-46ee-bbe7-63474f4b8673","year":2021},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.060365Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:2ffdb6ec1c756685c15c03bff05bcb7df316e9752d3fa02ae71a357e080af324","observation_id":"38b24e7d-81c9-407e-8caf-661deef146ba","resolution":{"observed_at":"2026-08-05T22:55:47.926042Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:45.129516Z","title":"Tsuchiya, T","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.129516Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:df9755ff1d1d20baabed59041cb80a14bcb4dfcc0c24feefa4ae8665435dd4a5","observation_id":"678d8891-9268-4eb7-aa79-9769f34f3399","resolution":{"observed_at":"2026-08-05T22:55:45.129516Z","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":"2019.88952","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:55:46.636932Z","title":"Gasparyan and H","venue":null,"work_id":"c711e9c1-8f14-46ce-8850-0ea737efceab","year":2019},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.176802Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:0e6ad07744507e57fb12a70890694ddc0acb50e41898df62db0f238aa0ac478e","observation_id":"b30e9895-7409-4976-8c8d-c52db47088e5","resolution":{"observed_at":"2026-08-05T22:55:46.851706Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.907038Z","title":null,"venue":null,"work_id":"1cdcdfea-2e43-46a3-8835-6b7219f0f027","year":1990},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.202524Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:13cc60b782affe8c36e2942d77a3bd75df5326cea391d59fb5154d5113ecad87","observation_id":"8554cca5-ab8b-4273-9a26-a8305254c9c7","resolution":{"observed_at":"2026-08-05T22:55:47.911403Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.893044Z","title":"Verschueren, G","venue":null,"work_id":"27eb5e51-7d7a-41d3-aae3-91683b163474","year":2021},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.253974Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:21d5216e50db3ae564881cc7ef606b89dc89ae783c5e58bb4dc22877581dad81","observation_id":"c89464db-c986-4309-92fe-f0f6a0fde0e2","resolution":{"observed_at":"2026-08-05T22:55:47.897218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:45.318504Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.318504Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:6fae33e5ce861774502a473310e7f97361d9674d00ef1729ab39370fe37a8783","observation_id":"b1fa863f-9b05-43f3-b379-4605587c0f78","resolution":{"observed_at":"2026-08-05T22:55:45.318504Z","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":"2026-08-05T22:55:47.877745Z","title":"Hochreiter and J","venue":null,"work_id":"1dc99456-cd16-43c5-af80-474cf17a1079","year":1997},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.366721Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:cee315330d855e17a8b37cafc700afee8a49e70f9e81e2c5a1d79756edb9887e","observation_id":"cd4c724b-c563-43d5-b499-2d7a5fdf6306","resolution":{"observed_at":"2026-08-05T22:55:47.882566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.01271","last_updated":"2018-04-19T14:32:38Z","snapshot_observed_at":"2026-08-13T10:37:24.864456Z","submitted_at":"2018-03-04T00:20:29Z","title":"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.01271","snapshot_observed_at":"2026-08-05T22:55:45.392531Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.392531Z"},"links":{"cited_paper":"/paper/1803.01271","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:a1fddb878df311d57d41a8f5c1b4ab36b167db9ca90f7b62f859007f387e80c9","observation_id":"e22e3733-d7de-4515-89ba-424d2e981e9c","resolution":{"observed_at":"2026-08-05T22:55:45.392531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.3555","last_updated":"2014-12-11T06:46:53Z","snapshot_observed_at":"2026-08-13T10:35:27.214652Z","submitted_at":"2014-12-11T06:46:53Z","title":"Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.3555","snapshot_observed_at":"2026-08-05T22:55:45.443727Z","title":"Chung, C","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.443727Z"},"links":{"cited_paper":"/paper/1412.3555","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:07b2e31e1cdd8c6a928f0e5bac6ad095339b68169fbd9aa9dff8ae4b39461eda","observation_id":"57249a43-1de4-4d2e-8c2b-367f68559875","resolution":{"observed_at":"2026-08-05T22:55:45.443727Z","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":"2026-08-05T22:55:47.863227Z","title":"Kicki, P","venue":null,"work_id":"32e94523-b325-4fb0-a7f1-6d6a4247ebe4","year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.490620Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:d381d68fbccad1c4fa3a7ffd1aaf24822fb1e1987fa6e1218e6b7091ea698007","observation_id":"86d3e988-10ab-4058-a9b1-24a12c998524","resolution":{"observed_at":"2026-08-05T22:55:47.867567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.849716Z","title":null,"venue":null,"work_id":"29911b55-10a0-40d6-81dc-4c4758c91981","year":2018},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.538176Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:5fd24120c483a5df0ed853f74b337a0f7fbc304d415a0500bad12067d79e995f","observation_id":"04fc6a2f-9de4-4427-8260-4baf85b5f0fe","resolution":{"observed_at":"2026-08-05T22:55:47.853819Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.17032","last_updated":"2025-11-02T13:42:19Z","snapshot_observed_at":"2026-08-13T22:24:37.672685Z","submitted_at":"2024-07-24T06:35:05Z","title":"Gymnasium: A Standard Interface for Reinforcement Learning Environments","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.17032","snapshot_observed_at":"2026-08-05T22:55:45.585412Z","title":"Towers, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.585412Z"},"links":{"cited_paper":"/paper/2407.17032","citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:bdfee92df6533fb10fc445294d985566d230e050306a9a301e6922ce2a98058a","observation_id":"cb093811-ecad-42aa-a04c-787d1acc17f1","resolution":{"observed_at":"2026-08-05T22:55:45.585412Z","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":"2026-08-05T22:55:47.835812Z","title":"Todorov, T","venue":null,"work_id":"079faeb4-3311-4b63-9ab3-098e899eda63","year":2012},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.630924Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:2b7b7dca7729eca1e90a57ec33d6dbbe49f240a0d8b8f2a5b9db4c861d1e131e","observation_id":"d3622652-a4ba-4210-a5bd-07e0cc3e7a96","resolution":{"observed_at":"2026-08-05T22:55:47.840071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.822157Z","title":"Liniger, A","venue":null,"work_id":"7fb47867-2011-45c6-b75b-27a904cc1993","year":2015},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.678256Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:c195fb2e076bd177244c7bdfff317d384fe15144a7aa9fb4f141c52d6c0b4717","observation_id":"ef6c3e2f-7a58-4a21-8459-5704d849d350","resolution":{"observed_at":"2026-08-05T22:55:47.826412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.807874Z","title":"Srinivasan, S","venue":null,"work_id":"c28b5c1e-6cae-46dc-9c3e-9e0ddd5dae57","year":2021},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.734618Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:398ede1667aaf6d735154233a27acd35972bcc9f0527fbba2bb9ca8f88c3c749","observation_id":"28cd430e-dfc9-471e-ae50-db4a423f8aac","resolution":{"observed_at":"2026-08-05T22:55:47.812196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.793411Z","title":null,"venue":null,"work_id":"e60b75f4-fb7e-4b5c-914f-8018436be285","year":2010},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.751503Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:fe262852fa3c4039bdafb6f48318da8324fd91b5b53412f9f88c76d6542f70e4","observation_id":"cd73f8c1-4a36-4204-a969-3342282ae1a8","resolution":{"observed_at":"2026-08-05T22:55:47.797650Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.779534Z","title":"Savitzky and M","venue":null,"work_id":"f7960aa6-3e53-4edf-b41d-5167a5f7ef77","year":1964},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.825653Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:d50fdbbcf77a193f01b1ca987e988cc67c6a3a81460baee5fc532535728b3942","observation_id":"9b08c528-6b7e-4994-a2a5-66cd4fe5b7bc","resolution":{"observed_at":"2026-08-05T22:55:47.783829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.764499Z","title":"Verschueren, S","venue":null,"work_id":"8c8c7da4-8a18-424e-86ca-01157f4b2cad","year":2014},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.850614Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:257ec5e816f7217bfc7db80e832f399321771f6e21ad3db40f1cc60f9e78c74a","observation_id":"32a363a9-6430-4448-b9e0-ced841d3e3fe","resolution":{"observed_at":"2026-08-05T22:55:47.769354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-05T22:55:47.749848Z","title":null,"venue":null,"work_id":"a3f0d9b9-90a0-4db8-83de-3f5cd0734ad9","year":2020},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:45.902406Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:528ed471daa73c8b074a2460a992d27c718cab374beb94018e0e4a9c8e1c78a5","observation_id":"9a3436ca-e310-490f-96fb-f2e2f6218938","resolution":{"observed_at":"2026-08-05T22:55:47.753964Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/b978-0-12-812693-6.00003-1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Balkwill","venue":"Elsevier eBooks","work_id":"652dad11-fcfe-4daf-a322-8783f968c855","year":2018},"citing_paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-05T22:55:46.049173Z"},"links":{"citing_paper":"/paper/2508.06181"},"observation_digest":"sha256:4bef5cdbd1e351e0223cc222af046925c8ad3676a7a6e095f2b13048a7745364","observation_id":"e3e5a575-69f5-4b70-ab71-034f5ff9bb30","resolution":{"observed_at":"2026-08-05T22:55:46.203489Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.06181","last_updated":"2025-08-08T09:53:46Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-13T12:48:03.711835Z","submitted_at":"2025-08-08T09:53:46Z","title":"Beyond Constant Parameters: Hyper Prediction Models and HyperMPC"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":14,"verified_exact":6,"verified_fuzzy":32},"total_outbound_references":54},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2508.06181."}