{"as_of":"2026-08-10T21:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a5f5235b2fb5cfeeac16cbba4d13a1fae3e04bab16188310f717f1aaa4f133ab","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":"2026-08-10T06:31:04.303077+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":"2026-08-06T23:40:38.951596Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":1,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-06T23:40:38.951596Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.16555","last_updated":"2025-06-19T19:19:27Z","snapshot_observed_at":"2026-08-06T23:35:49.797948Z","submitted_at":"2025-06-19T19:19:27Z","title":"An Optimization-Augmented Control Framework for Single and Coordinated Multi-Arm Robotic Manipulation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T23:40:38.951596Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2506.16555"},"observation_digest":"sha256:3027551e120883618e124923b26f685b54dd13b5d2d261a593b08d78213ee11e","observation_id":"db7fa22e-4363-4dc4-8a52-b7b00e31c04f","resolution":{"observed_at":"2026-08-06T23:40:38.951596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-06T20:53:59.371701Z","title":"Adaptive compliance policy: Learning approximate compliance for diffusion guided control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01723","last_updated":"2025-07-02T13:58:15Z","snapshot_observed_at":"2026-08-06T20:42:03.813769Z","submitted_at":"2025-07-02T13:58:15Z","title":"SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T20:53:59.371701Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2507.01723"},"observation_digest":"sha256:d325b20265170dc3ca01618b8b7e857588090b69b36dbfcd39a2a179a24f8dff","observation_id":"4d27e84e-cb74-4b08-9526-35ea65688570","resolution":{"observed_at":"2026-08-06T20:53:59.371701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-04T21:29:09.775379Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.07962","last_updated":"2025-09-09T17:50:37Z","snapshot_observed_at":"2026-08-04T21:29:05.648300Z","submitted_at":"2025-09-09T17:50:37Z","title":"TA-VLA: Elucidating the Design Space of Torque-aware Vision-Language-Action Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T21:29:09.775379Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2509.07962"},"observation_digest":"sha256:d77099dcc6feb1e5b67c7eda49c8a8cb92e11572d7049c5c3c7b91d014b812f9","observation_id":"81795942-73db-42a6-9c83-3496fc33fac6","resolution":{"observed_at":"2026-08-04T21:29:09.775379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":"2410.09309","doi":"10.48550/arxiv.2410.09309","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptive compliance policy: Learning approximate compliance for diffusion guided control","venue":"arXiv (Cornell University)","work_id":"8e2d090c-fade-486a-a58f-c39a33fc78b5","year":2024},"citing_paper":{"arxiv_id":"2510.02738","last_updated":"2026-04-16T01:39:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-10-03T05:40:58Z","title":"Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-18T11:07:57.386640Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2510.02738"},"observation_digest":"sha256:30c1a872fea9feb2ca36102a8eb04d88af10c8f60e7a5ba8a37c54fd176ce1c4","observation_id":"2a8811a1-2486-4741-af01-4274043f4379","resolution":{"observed_at":"2026-05-18T11:11:18.021843Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":"2410.09309","doi":"10.48550/arxiv.2410.09309","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptive compliance policy: Learning approximate compliance for diffusion guided control","venue":"arXiv (Cornell University)","work_id":"8e2d090c-fade-486a-a58f-c39a33fc78b5","year":2024},"citing_paper":{"arxiv_id":"2604.10647","last_updated":"2026-05-05T07:14:11Z","snapshot_observed_at":"2026-07-06T22:59:13.936436Z","submitted_at":"2026-04-12T13:48:48Z","title":"OmniUMI: Towards Physically Grounded Robot Learning via Human-Aligned Multimodal Interaction","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T16:05:22.891661Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2604.10647"},"observation_digest":"sha256:77b124d1d47c43c9cb0d01c7a577fe3daaa59fa70f354dc49568d8b54976a346","observation_id":"def02fca-3be9-4620-8256-2dad03e67c3e","resolution":{"observed_at":"2026-05-11T09:21:00.351941Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":"2410.09309","doi":"10.48550/arxiv.2410.09309","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptive compliance policy: Learning approximate compliance for diffusion guided control","venue":"arXiv (Cornell University)","work_id":"8e2d090c-fade-486a-a58f-c39a33fc78b5","year":2024},"citing_paper":{"arxiv_id":"2604.22551","last_updated":"2026-04-24T13:45:04Z","snapshot_observed_at":"2026-08-03T02:55:51.041095Z","submitted_at":"2026-04-24T13:45:04Z","title":"QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-08T11:22:38.704101Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2604.22551"},"observation_digest":"sha256:5da35be51f906a1f0799676bfdbde46b6f2119feabf6785ab4092df6ad1b2427","observation_id":"03b293c7-2bec-4127-a5c9-d9ea25bf30af","resolution":{"observed_at":"2026-05-08T21:49:16.069574Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":"2410.09309","doi":"10.48550/arxiv.2410.09309","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adaptive compliance policy: Learning approximate compliance for diffusion guided control","venue":"arXiv (Cornell University)","work_id":"8e2d090c-fade-486a-a58f-c39a33fc78b5","year":2024},"citing_paper":{"arxiv_id":"2605.31321","last_updated":"2026-05-29T13:54:21Z","snapshot_observed_at":"2026-08-07T16:52:12.952570Z","submitted_at":"2026-05-29T13:54:21Z","title":"Surface Constraint Policy for Learning Surface-Constrained and Dynamically Feasible Robot Skills","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-28T21:53:36.465761Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2605.31321"},"observation_digest":"sha256:9d8181373c9845a4d65519d6900398ef6313d83ddec5b74d0e0f724a2a6b842b","observation_id":"b94d7f39-573a-4719-9111-b4cf1c62317f","resolution":{"observed_at":"2026-07-01T19:56:11.202658Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09309","snapshot_observed_at":"2026-07-30T12:42:18.448920Z","title":"Adaptive compliance policy: Learning approximate compliance for diffusion guided control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23783","last_updated":"2026-07-26T17:58:53Z","snapshot_observed_at":"2026-08-07T01:32:38.441854Z","submitted_at":"2026-07-26T17:58:53Z","title":"$N_0$-TWAM: Scaling Tactile-Native World-Action Model for Contact-Rich Manipulation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-30T12:42:18.448920Z"},"links":{"cited_paper":"/paper/2410.09309","citing_paper":"/paper/2607.23783"},"observation_digest":"sha256:86cdf3d4483bd38e811cb24d183987920751b7bd771292230492098e305732b4","observation_id":"d7d14adb-428f-4e5e-8f57-0bab6bcc443d","resolution":{"observed_at":"2026-07-30T12:42:18.448920Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.09309/citation-record","integrity":"/paper/2410.09309/integrity","json":"/paper/2410.09309/citation-record.json","paper":"/paper/2410.09309"},"outbound":[],"paper":{"arxiv_id":"2410.09309","last_updated":"2025-03-07T00:24:52Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-10T10:17:17.771774Z","submitted_at":"2024-10-12T00:08:18Z","title":"Adaptive Compliance Policy: Learning Approximate Compliance for Diffusion Guided Control"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.09309."}