{"as_of":"2026-08-09T23:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aad157d9bd6d15d0f4f949f11839856c5bddc692a5cf2274b7a9aaf075cc5263","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:59:19.748708Z","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":"2026-05-19T17:27:41.391516Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-08-07T13:59:19.748708Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20424","last_updated":"2025-07-23T17:39:54Z","snapshot_observed_at":"2026-08-08T15:06:50.434347Z","submitted_at":"2025-05-26T18:17:07Z","title":"Robot Operation of Home Appliances by Reading User Manuals","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:59:19.748708Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2505.20424"},"observation_digest":"sha256:18efd3bed0c862500bec3677e31a9a747c7a61da9364377bd1c3fba3359c945d","observation_id":"208b0b91-8c93-4c94-8185-a9ad2cfaef2b","resolution":{"observed_at":"2026-08-07T13:59:19.748708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-08-04T18:58:13.014011Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09560","last_updated":"2025-09-11T15:51:43Z","snapshot_observed_at":"2026-08-09T19:31:23.395714Z","submitted_at":"2025-09-11T15:51:43Z","title":"Boosting Embodied AI Agents through Perception-Generation Disaggregation and Asynchronous Pipeline Execution","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-04T18:58:13.014011Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2509.09560"},"observation_digest":"sha256:e6687e5733056bb0c9c951129a897677d992f86e352995dda009edad226a4595","observation_id":"c2663ad4-79b1-4a8a-bea8-b8ab73bd2115","resolution":{"observed_at":"2026-08-04T18:58:13.014011Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":"2410.12782","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context learning enables robot action prediction in llms","venue":null,"work_id":"c035156a-23fa-4e1e-b859-e5f24bf1a615","year":2024},"citing_paper":{"arxiv_id":"2602.13193","last_updated":"2026-04-06T03:04:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-13T18:57:56Z","title":"Steerable Vision-Language-Action Policies for Embodied Reasoning and Hierarchical Control","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-15T22:05:39.797848Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2602.13193"},"observation_digest":"sha256:4ecd980502c24d2038b38a2c97f9ff6642057407153bfb189ded6e1148d82512","observation_id":"0f7fd599-39e8-4089-95e5-c2619fdc35a4","resolution":{"observed_at":"2026-05-15T22:06:42.889288Z","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":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":"2410.12782","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context learning enables robot action prediction in llms","venue":null,"work_id":"c035156a-23fa-4e1e-b859-e5f24bf1a615","year":2024},"citing_paper":{"arxiv_id":"2604.15215","last_updated":"2026-05-29T06:48:30Z","snapshot_observed_at":"2026-07-12T19:46:45.862744Z","submitted_at":"2026-04-16T16:47:08Z","title":"A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T10:47:05.008564Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2604.15215"},"observation_digest":"sha256:5ca9f5cf25f423dfc1bd2bac452fa95afaa506980efcf6051326aac57f3823b6","observation_id":"c297cd50-d56b-4407-8a89-5cff410078db","resolution":{"observed_at":"2026-05-10T10:49:56.288249Z","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":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":"2410.12782","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context learning enables robot action prediction in llms","venue":null,"work_id":"c035156a-23fa-4e1e-b859-e5f24bf1a615","year":2024},"citing_paper":{"arxiv_id":"2604.15215","last_updated":"2026-05-29T06:48:30Z","snapshot_observed_at":"2026-07-12T19:46:45.862744Z","submitted_at":"2026-04-16T16:47:08Z","title":"A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-19T17:24:01.180062Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2604.15215"},"observation_digest":"sha256:444743b85afb0c369a07b40928f945e49ef5735590f6baddbd46b29819969cb0","observation_id":"fcdda2f7-acbb-4af6-a413-02c35fc1e74d","resolution":{"observed_at":"2026-05-19T17:27:41.393259Z","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":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":"2410.12782","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context learning enables robot action prediction in llms","venue":null,"work_id":"c035156a-23fa-4e1e-b859-e5f24bf1a615","year":2024},"citing_paper":{"arxiv_id":"2605.01448","last_updated":"2026-05-02T13:55:28Z","snapshot_observed_at":"2026-07-06T23:14:38.379875Z","submitted_at":"2026-05-02T13:55:28Z","title":"Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-09T14:30:00.890117Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2605.01448"},"observation_digest":"sha256:f0eac90cbee1d8d88e9a0f7c3910d0f2b30059def94f5fa55d280ea246c46ebf","observation_id":"a05e4939-67d0-43f4-ba0d-eaf8d5cf4190","resolution":{"observed_at":"2026-05-11T16:56:06.899468Z","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":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":"2410.12782","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context learning enables robot action prediction in llms","venue":null,"work_id":"c035156a-23fa-4e1e-b859-e5f24bf1a615","year":2024},"citing_paper":{"arxiv_id":"2605.05115","last_updated":"2026-05-06T16:46:03Z","snapshot_observed_at":"2026-08-07T10:12:24.411121Z","submitted_at":"2026-05-06T16:46:03Z","title":"Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior","version":1},"reference_index":262,"source":"arxiv_source","source_observed_at":"2026-05-08T17:47:09.591001Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2605.05115"},"observation_digest":"sha256:bd8bc6cb2c0c26926ac4cf3c4cd970d5d0d5e535881e0976b7bfbea38e9d00e7","observation_id":"24e89c0d-46f5-4c12-9a56-f736d7117a90","resolution":{"observed_at":"2026-05-11T17:16:06.701430Z","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":"2410.12782","last_updated":"2025-03-17T10:43:54Z","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs","version":2},"cited_work":{"arxiv_id":"2410.12782","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.12782","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-context learning enables robot action prediction in llms","venue":null,"work_id":"c035156a-23fa-4e1e-b859-e5f24bf1a615","year":2024},"citing_paper":{"arxiv_id":"2605.12412","last_updated":"2026-05-12T17:09:41Z","snapshot_observed_at":"2026-07-06T23:24:08.763444Z","submitted_at":"2026-05-12T17:09:41Z","title":"Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-05-13T05:17:34.283917Z"},"links":{"cited_paper":"/paper/2410.12782","citing_paper":"/paper/2605.12412"},"observation_digest":"sha256:57ad72903f26984039c43f57ec706779ab64f896e9fb3ebb8b5d20ac4f2b977f","observation_id":"2828e491-4311-47be-b35a-64adc3e6233a","resolution":{"observed_at":"2026-05-13T05:27:19.300758Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2410.12782/citation-record","integrity":"/paper/2410.12782/integrity","json":"/paper/2410.12782/citation-record.json","paper":"/paper/2410.12782"},"outbound":[],"paper":{"arxiv_id":"2410.12782","last_updated":"2025-03-17T10:43:54Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-08T18:41:54.491013Z","submitted_at":"2024-10-16T17:56:49Z","title":"In-Context Learning Enables Robot Action Prediction in LLMs"},"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 8 inbound Pith citation observations for arXiv:2410.12782."}