{"as_of":"2026-08-09T15:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec72af15c99973d67f35e026c0364aeac936573b41ab91d9c2ac736d0b708e3a","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T00:39:32.867983Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2608.05720/citation-record","integrity":"/paper/2608.05720/integrity","json":"/paper/2608.05720/citation-record.json","paper":"/paper/2608.05720"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:39:32.815745Z","title":"2023.XIX.026","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.815745Z"},"links":{"citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:adfb264d1b6154de0034fca60e5fd288400b8c64bc5736610f861b82859da958","observation_id":"beef837d-5304-4529-a197-ff146b3ab192","resolution":{"observed_at":"2026-08-08T00:39:32.815745Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.20104","last_updated":"2026-06-18T11:25:16Z","snapshot_observed_at":"2026-08-02T12:07:11.942278Z","submitted_at":"2026-06-18T11:25:16Z","title":"Sensorimotor World Models: Perception for Action via Inverse Dynamics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.20104","snapshot_observed_at":"2026-08-08T00:39:32.822029Z","title":"Sensorimotor world models: Perception for action via inverse dynamics","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.822029Z"},"links":{"cited_paper":"/paper/2606.20104","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:a6d9e236b1a53a22846e35745d4fccfcda30297f4d51a97ea4498627a4655f7d","observation_id":"65bbb1aa-810d-4aee-b274-d8deee1a22d0","resolution":{"observed_at":"2026-08-08T00:39:32.822029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2603.19312","last_updated":"2026-06-03T18:50:40Z","snapshot_observed_at":"2026-08-06T05:42:53.129146Z","submitted_at":"2026-03-13T19:48:14Z","title":"LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2603.19312","snapshot_observed_at":"2026-08-08T00:39:32.833028Z","title":"LeWorld- Model: Stable end-to-end joint-embedding predictive architecture from pixels","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.833028Z"},"links":{"cited_paper":"/paper/2603.19312","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:61efd1923fcb537077703e197319accd3e47086285b97c3018518380ed3f7fd9","observation_id":"d4a868a5-d85c-4510-be7b-5610287c5f9b","resolution":{"observed_at":"2026-08-08T00:39:32.833028Z","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":"2026-08-08T00:39:33.248482Z","title":"ds denotes the task-speciﬁc physical-target dimension","venue":null,"work_id":"b19518c0-7d4b-4a1e-90b5-48df5504c193","year":2025},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.862502Z"},"links":{"citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:efcee106a3239310d07e6804d8cb73edcbb389a9e42aa50d024026b4627976e0","observation_id":"42810212-4665-477a-8807-9e114ef935bc","resolution":{"observed_at":"2026-08-08T00:39:33.253438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:39:33.230444Z","title":"The action-query module forms a single query from the temporal mean of the context action embeddings and uses the latent sequence as keys and values","venue":null,"work_id":"7eb3ed6b-1ab3-4175-8487-6970fb51c3e1","year":2025},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":192,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.867983Z"},"links":{"citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:0a4709ccce7df8fe183e942f6ed3c8b9633f9a8404e6e55699ffebc2bc2b3758","observation_id":"48b70421-315f-4686-9479-1d6b628f6f0e","resolution":{"observed_at":"2026-08-08T00:39:33.236111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:39:32.827492Z","title":"12 Published as a conference paper at ICLR 2025 Y ann LeCun","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.827492Z"},"links":{"citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:55b8f3b6be82476e120d994d4aed9d24101d40ba4e49756d1faafceb00b9a356","observation_id":"02ce7373-cda4-4782-887b-78038bbe21e6","resolution":{"observed_at":"2026-08-08T00:39:32.827492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.31111","last_updated":"2026-05-29T10:23:48Z","snapshot_observed_at":"2026-08-03T08:44:30.193764Z","submitted_at":"2026-05-29T10:23:48Z","title":"Subspace-Decomposed JEPAs: Disentangling Progression and Content in Latent World Models","version":1},"cited_work":{"arxiv_id":"2605.31111","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.31111","snapshot_observed_at":"2026-08-08T00:39:33.128587Z","title":"Subspace-Decomposed JEPAs: Disentangling Progression and Content in Latent World Models","venue":"cs.LG","work_id":"5db98ada-9a47-4461-8738-fb91b235cb6e","year":2026},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.839545Z"},"links":{"cited_paper":"/paper/2605.31111","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:083623041bba5e66690d697f5ceda9c94de9adc7f7c442d97608187dd45332c8","observation_id":"2d88e2fe-6a87-4127-bcfe-fd9e51485f6c","resolution":{"observed_at":"2026-08-08T00:39:33.136146Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:39:32.845372Z","title":"Aaron van den Oord, Y azhe Li, and Oriol Vinyals","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.845372Z"},"links":{"citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:4aaf7ee69bd09fe3e0c2a74ca6077737fe27b042fab3c85c558685722723bf3f","observation_id":"897d17bf-552a-4fbd-938a-11c5688933b8","resolution":{"observed_at":"2026-08-08T00:39:32.845372Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.09241","last_updated":"2026-05-10T00:51:47Z","snapshot_observed_at":"2026-07-06T23:21:21.560069Z","submitted_at":"2026-05-10T00:51:47Z","title":"Sub-JEPA: Subspace Gaussian Regularization for Stable End-to-End World Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.09241","snapshot_observed_at":"2026-08-08T00:39:32.850936Z","title":"Sub-JEPA: Subspace gaussian regularization for stable end-to-end world models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.850936Z"},"links":{"cited_paper":"/paper/2605.09241","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:d293d3fed9eb90a0d438daa518e2d4f9f6d66c578a0ab7add46196ebbb083c3e","observation_id":"c507d054-03a0-4288-abc1-e3ed926d0166","resolution":{"observed_at":"2026-08-08T00:39:32.850936Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08471","last_updated":"2024-02-15T18:59:11Z","snapshot_observed_at":"2026-08-07T02:30:11.447693Z","submitted_at":"2024-02-15T18:59:11Z","title":"Revisiting Feature Prediction for Learning Visual Representations from Video","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.08471","snapshot_observed_at":"2026-08-08T00:39:32.809493Z","title":"Revisiting feature prediction for learning visual representations from video","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.809493Z"},"links":{"cited_paper":"/paper/2404.08471","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:d0ba8d132f198f454b8f1d584dfde8f506d929af2581a9571b87c84cb2c8106f","observation_id":"5c6a4bbc-d208-42b6-9419-02e165346e79","resolution":{"observed_at":"2026-08-08T00:39:32.809493Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09985","last_updated":"2025-06-11T17:57:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-11T17:57:09Z","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09985","snapshot_observed_at":"2026-08-08T00:39:32.797918Z","title":"V-JEPA 2: Self-supervised video models enable understanding, prediction and planning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.797918Z"},"links":{"cited_paper":"/paper/2506.09985","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:217f2485659e6c49d2fb97cd0baca8c4dd138d58b7486dbc5dedbae9f84d2a0f","observation_id":"d659385f-b7e5-4005-aad6-c547b7ef764f","resolution":{"observed_at":"2026-08-08T00:39:32.797918Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.08544","last_updated":"2025-11-14T08:38:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-11T18:21:55Z","title":"LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.08544","snapshot_observed_at":"2026-08-08T00:39:32.803846Z","title":"LeJEPA: Provable and scalable self-supervised learning with- out the heuristics","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.803846Z"},"links":{"cited_paper":"/paper/2511.08544","citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:1a80a41a1e619d2ec8ae560f89bb1521843f3a5104d344927137fe4fa54f71d5","observation_id":"307e0ff8-9b1e-4fc2-9cba-5cf66c351bd2","resolution":{"observed_at":"2026-08-08T00:39:32.803846Z","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":"2026-08-08T00:39:33.264395Z","title":"Table 6: Notation used in PhyLatent","venue":null,"work_id":"139d2539-8c23-4f52-a8c8-bc8930693884","year":2025},"citing_paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-08T00:39:32.856822Z"},"links":{"citing_paper":"/paper/2608.05720"},"observation_digest":"sha256:da113da4eb3275edc487260799be9c6d21bb9911f01585380714c98a942f1ad0","observation_id":"304c76e7-323e-475e-90f5-775a4b69a31f","resolution":{"observed_at":"2026-08-08T00:39:33.270283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}}],"paper":{"arxiv_id":"2608.05720","last_updated":"2026-08-06T08:02:15Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T14:10:54.889920Z","submitted_at":"2026-08-06T08:02:15Z","title":"PhyLatent: Learning Dynamics-Relevant Representations for JEPA World Models"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":1,"verified_fuzzy":3},"total_outbound_references":13},"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 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2608.05720."}