{"as_of":"2026-08-09T22:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6850b410c4c206af71bfbb72a5b93080c16d63cd3aeb5c221bf7f5be5a384d84","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:53:54.825537Z","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":"2026-07-04T04:39:33.914861Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":"2412.08442","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-07-04T04:39:33.914861Z","title":"From multimodal llms to generalist embodied agents: Methods and lessons","venue":null,"work_id":"3734e67c-28ff-407a-a15b-741504941b0c","year":2024},"citing_paper":{"arxiv_id":"2504.16054","last_updated":"2025-04-22T17:31:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-22T17:31:29Z","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-22T18:02:23.305313Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2504.16054"},"observation_digest":"sha256:b9d1c97111cd55c63e0d6f6155ac9911eb4e91075c5e69c0f3af2fac61429c5e","observation_id":"a427c21b-8a0f-4bcb-9ca1-c34cf5463855","resolution":{"observed_at":"2026-05-22T18:05:00.858804Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-08-07T13:53:54.825537Z","title":"From multimodal llms to generalist embodied agents: Methods and lessons","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20726","last_updated":"2025-07-29T02:51:37Z","snapshot_observed_at":"2026-08-07T22:45:15.753079Z","submitted_at":"2025-05-27T05:14:50Z","title":"ManiTaskGen: A Comprehensive Task Generator for Benchmarking and Improving Vision-Language Agents on Embodied Decision-Making","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:53:54.825537Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2505.20726"},"observation_digest":"sha256:07754b2d032975081382d2fb1478386998f42d9c98039c6548da580004a2a3fd","observation_id":"a672600d-eea8-4f3d-a679-ce150f1dfb45","resolution":{"observed_at":"2026-08-07T13:53:54.825537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-08-07T12:45:23.965626Z","title":"From multimodal llms to generalist embodied agents: Methods and lessons","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23705","last_updated":"2025-05-29T17:40:09Z","snapshot_observed_at":"2026-08-07T12:37:05.162590Z","submitted_at":"2025-05-29T17:40:09Z","title":"Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.965626Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2505.23705"},"observation_digest":"sha256:dd79cfb1e10a07a40de0ded1643339eaf5b7d493cc2d1598a4fa0b2ebb66b3d5","observation_id":"42cb4d42-bbdd-4218-9e25-dc0bd74d1b1d","resolution":{"observed_at":"2026-08-07T12:45:23.965626Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-08-07T05:43:14.217713Z","title":"Devon Hjelm, Zhe Gan, Zsolt Kira, and Alexander Toshev","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07223","last_updated":"2025-06-08T17:09:26Z","snapshot_observed_at":"2026-08-09T17:00:50.402733Z","submitted_at":"2025-06-08T17:09:26Z","title":"LLM-Enhanced Rapid-Reflex Async-Reflect Embodied Agent for Real-Time Decision-Making in Dynamically Changing Environments","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:43:14.217713Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2506.07223"},"observation_digest":"sha256:a409fd4e14e1dc38eb13bd25a856c75a916fea3f123686b77c292da040f81818","observation_id":"d64e2629-ea18-4e73-ac59-64eba5abd7ba","resolution":{"observed_at":"2026-08-07T05:43:14.217713Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":"2412.08442","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-07-04T04:39:33.914861Z","title":"From multimodal llms to generalist embodied agents: Methods and lessons","venue":null,"work_id":"3734e67c-28ff-407a-a15b-741504941b0c","year":2024},"citing_paper":{"arxiv_id":"2507.16815","last_updated":"2025-09-18T16:26:53Z","snapshot_observed_at":"2026-08-03T17:16:24.219569Z","submitted_at":"2025-07-22T17:59:46Z","title":"ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-19T03:18:14.655384Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2507.16815"},"observation_digest":"sha256:8d45b041ec60d28d031552431492c71111d40ae758786d94420ca0aba535ec32","observation_id":"90df1a9d-3276-4332-8d9f-e90baab03630","resolution":{"observed_at":"2026-05-19T03:22:01.009006Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":"2412.08442","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-07-04T04:39:33.914861Z","title":"From multimodal llms to generalist embodied agents: Methods and lessons","venue":null,"work_id":"3734e67c-28ff-407a-a15b-741504941b0c","year":2024},"citing_paper":{"arxiv_id":"2606.00110","last_updated":"2026-05-27T03:38:15Z","snapshot_observed_at":"2026-08-06T22:19:24.528783Z","submitted_at":"2026-05-27T03:38:15Z","title":"General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling","version":1},"reference_index":154,"source":"arxiv_source","source_observed_at":"2026-06-29T13:33:03.368006Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2606.00110"},"observation_digest":"sha256:55001d3339c419b1adee05a210d924876e9ffdf453527444676833d30d10ee6b","observation_id":"99799768-9768-4243-a64d-8d2c35cd9273","resolution":{"observed_at":"2026-06-29T13:33:27.837709Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2412.08442","last_updated":"2024-12-11T15:06:25Z","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons","version":1},"cited_work":{"arxiv_id":"2412.08442","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.08442","snapshot_observed_at":"2026-07-04T04:39:33.914861Z","title":"From multimodal llms to generalist embodied agents: Methods and lessons","venue":null,"work_id":"3734e67c-28ff-407a-a15b-741504941b0c","year":2024},"citing_paper":{"arxiv_id":"2606.20905","last_updated":"2026-06-18T20:01:32Z","snapshot_observed_at":"2026-08-03T03:13:19.923134Z","submitted_at":"2026-06-18T20:01:32Z","title":"Vesta: A Generalist Embodied Reasoning Model","version":1},"reference_index":106,"source":"pdf_text","source_observed_at":"2026-06-26T16:55:12.518255Z"},"links":{"cited_paper":"/paper/2412.08442","citing_paper":"/paper/2606.20905"},"observation_digest":"sha256:af76e249e1c9796beb8948d480518c2d6fa0dcf74e9183776e59423437eb2e2a","observation_id":"3f4b65fa-8d09-4ca2-ae5b-cec0a03d3eca","resolution":{"observed_at":"2026-07-04T04:39:33.921356Z","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/2412.08442/citation-record","integrity":"/paper/2412.08442/integrity","json":"/paper/2412.08442/citation-record.json","paper":"/paper/2412.08442"},"outbound":[],"paper":{"arxiv_id":"2412.08442","last_updated":"2024-12-11T15:06:25Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T20:05:18.939982Z","submitted_at":"2024-12-11T15:06:25Z","title":"From Multimodal LLMs to Generalist Embodied Agents: Methods and Lessons"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2412.08442."}