{"as_of":"2026-08-10T14:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:356d5c64adf3d1b86435e29c86537a9eb365bfe6270984d3b33c8f8ffc3d39cb","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T19:18:44.910833Z","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":"2026-07-02T12:36:57.220166Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.12192","last_updated":"2024-10-30T18:48:00Z","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12192","snapshot_observed_at":"2026-08-09T19:18:44.910833Z","title":"J., Pan, H., Iyer, A., Haldar, S., and Pinto, L","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00379","last_updated":"2025-06-12T16:28:52Z","snapshot_observed_at":"2026-08-10T10:34:42.717916Z","submitted_at":"2025-02-01T09:35:51Z","title":"Latent Action Learning Requires Supervision in the Presence of Distractors","version":5},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-09T19:18:44.910833Z"},"links":{"cited_paper":"/paper/2409.12192","citing_paper":"/paper/2502.00379"},"observation_digest":"sha256:4151f7bc8c534fa6032a84c38a07d338959f3877f322aef3a9374fde311572b2","observation_id":"3b030eb7-2d58-47a4-a126-9588f4679459","resolution":{"observed_at":"2026-08-09T19:18:44.910833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12192","last_updated":"2024-10-30T18:48:00Z","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control","version":2},"cited_work":{"arxiv_id":"2409.12192","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.12192","snapshot_observed_at":"2026-07-02T12:36:57.220166Z","title":"Dynamo: In-domain dynamics pretraining for visuo-motor control","venue":null,"work_id":"67ba5b7f-a62f-4992-a0d7-39d4fdb48c3e","year":2024},"citing_paper":{"arxiv_id":"2602.20231","last_updated":"2026-04-09T04:26:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-23T18:41:41Z","title":"UniLACT: Depth-Aware RGB Latent Action Learning for Vision-Language-Action Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-15T20:18:31.988002Z"},"links":{"cited_paper":"/paper/2409.12192","citing_paper":"/paper/2602.20231"},"observation_digest":"sha256:2ca2f2b01f8b484aceefc7457855a80221df642776ddeab602e1d82065322429","observation_id":"0e9a90be-b504-4c6a-b4b2-0f351790537f","resolution":{"observed_at":"2026-05-15T20:20:17.647274Z","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":"2409.12192","last_updated":"2024-10-30T18:48:00Z","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control","version":2},"cited_work":{"arxiv_id":"2409.12192","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.12192","snapshot_observed_at":"2026-07-02T12:36:57.220166Z","title":"Dynamo: In-domain dynamics pretraining for visuo-motor control","venue":null,"work_id":"67ba5b7f-a62f-4992-a0d7-39d4fdb48c3e","year":2024},"citing_paper":{"arxiv_id":"2605.20223","last_updated":"2026-05-13T09:54:35Z","snapshot_observed_at":"2026-08-04T21:33:44.390576Z","submitted_at":"2026-05-13T09:54:35Z","title":"Why Latent Actions Fail, and How to Prevent It","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-21T08:33:02.745886Z"},"links":{"cited_paper":"/paper/2409.12192","citing_paper":"/paper/2605.20223"},"observation_digest":"sha256:82fbd718ac3c12a1f70dabb905778b8b2d8adfcc518518c99704adddbabd2907","observation_id":"acecdf49-faa0-43a5-bff0-03ede5a11b78","resolution":{"observed_at":"2026-05-21T08:34:05.326386Z","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":"2409.12192","last_updated":"2024-10-30T18:48:00Z","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control","version":2},"cited_work":{"arxiv_id":"2409.12192","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.12192","snapshot_observed_at":"2026-07-02T12:36:57.220166Z","title":"Dynamo: In-domain dynamics pretraining for visuo-motor control","venue":null,"work_id":"67ba5b7f-a62f-4992-a0d7-39d4fdb48c3e","year":2024},"citing_paper":{"arxiv_id":"2606.04130","last_updated":"2026-06-02T18:40:24Z","snapshot_observed_at":"2026-07-06T23:44:19.059079Z","submitted_at":"2026-06-02T18:40:24Z","title":"CLAW: Learning Continuous Latent Action World Models via Adversarial Latent Regularization","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-28T09:55:00.402411Z"},"links":{"cited_paper":"/paper/2409.12192","citing_paper":"/paper/2606.04130"},"observation_digest":"sha256:3603b1a842e0fbf7c1989fcf71d02685ff0cb2749eca2e081b1bc4a6afe8fbdf","observation_id":"398059aa-8ea1-4eed-aa47-375cec6dcb88","resolution":{"observed_at":"2026-07-02T03:36:29.611082Z","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":"2409.12192","last_updated":"2024-10-30T18:48:00Z","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control","version":2},"cited_work":{"arxiv_id":"2409.12192","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.12192","snapshot_observed_at":"2026-07-02T12:36:57.220166Z","title":"Dynamo: In-domain dynamics pretraining for visuo-motor control","venue":null,"work_id":"67ba5b7f-a62f-4992-a0d7-39d4fdb48c3e","year":2024},"citing_paper":{"arxiv_id":"2606.06100","last_updated":"2026-06-04T12:40:15Z","snapshot_observed_at":"2026-08-08T01:36:46.843343Z","submitted_at":"2026-06-04T12:40:15Z","title":"HyperVis: Continuous Latent Visual Relational Graphs on the Lorentz Hyperboloid for Compositional Reasoning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-28T01:57:27.102124Z"},"links":{"cited_paper":"/paper/2409.12192","citing_paper":"/paper/2606.06100"},"observation_digest":"sha256:bc782d3c8940f009d06f41d0f2b261f9185e1bda7c0844bb87b1c1d635eca767","observation_id":"36162ab0-8a56-4bf3-8c08-c1985a5f5688","resolution":{"observed_at":"2026-07-02T12:36:57.221781Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2409.12192","last_updated":"2024-10-30T18:48:00Z","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12192","snapshot_observed_at":"2026-08-01T15:40:51.382895Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.18236","last_updated":"2026-07-20T17:59:41Z","snapshot_observed_at":"2026-08-06T03:29:10.545879Z","submitted_at":"2026-07-20T17:59:41Z","title":"Patch Policy: Efficient Embodied Control via Dense Visual Representations","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T15:40:51.382895Z"},"links":{"cited_paper":"/paper/2409.12192","citing_paper":"/paper/2607.18236"},"observation_digest":"sha256:30f0d36e708aeefab36d1db12ee5eaf9439b926e287b7007fa90b029a1ee7ff7","observation_id":"80919815-5340-42ba-b48d-721840aebdbf","resolution":{"observed_at":"2026-08-01T15:40:51.382895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2409.12192/citation-record","integrity":"/paper/2409.12192/integrity","json":"/paper/2409.12192/citation-record.json","paper":"/paper/2409.12192"},"outbound":[],"paper":{"arxiv_id":"2409.12192","last_updated":"2024-10-30T18:48:00Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-08T15:23:46.399280Z","submitted_at":"2024-09-18T17:59:43Z","title":"DynaMo: In-Domain Dynamics Pretraining for Visuo-Motor 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 6 inbound Pith citation observations for arXiv:2409.12192."}