{"as_of":"2026-08-07T10:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:538e413fbe78350c7c7959849583feced5c507985d4893afd90833c769fc11f9","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:01:06.025052Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T20:01:07.601827Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2301.03949","last_updated":"2023-03-28T08:26:30Z","snapshot_observed_at":"2026-07-06T14:39:57.552494Z","submitted_at":"2023-01-10T13:15:42Z","title":"Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models","version":2},"cited_work":{"arxiv_id":"2301.03949","doi":null,"metadata_source":"pith","pith_arxiv_id":"2301.03949","snapshot_observed_at":"2026-08-06T20:01:07.601827Z","title":"Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models","venue":"cs.CV","work_id":"105b575c-49df-43ec-a67e-dc965e4b94b9","year":2023},"citing_paper":{"arxiv_id":"2507.04062","last_updated":"2025-07-05T14:57:37Z","snapshot_observed_at":"2026-08-06T19:54:14.061868Z","submitted_at":"2025-07-05T14:57:37Z","title":"Stochastic Human Motion Prediction with Memory of Action Transition and Action Characteristic","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T20:01:06.025052Z"},"links":{"cited_paper":"/paper/2301.03949","citing_paper":"/paper/2507.04062"},"observation_digest":"sha256:d38e1f3709fea9b3cc2a23b5ceeb09d8ad73fb84133610ee794ed2bdda06cb6b","observation_id":"1e4acf1e-01b4-40a7-ac71-acb1b2fe260f","resolution":{"observed_at":"2026-08-06T20:01:07.695771Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.03949","last_updated":"2023-03-28T08:26:30Z","snapshot_observed_at":"2026-07-06T14:39:57.552494Z","submitted_at":"2023-01-10T13:15:42Z","title":"Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.03949","snapshot_observed_at":"2026-08-03T16:52:07.925279Z","title":"arXiv:2301.03949 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11654","last_updated":"2026-07-29T10:20:14Z","snapshot_observed_at":"2026-08-06T11:27:45.019916Z","submitted_at":"2025-12-12T15:32:28Z","title":"Kinetic Mining in Context: Few-Shot Action Synthesis via Text-to-Motion Distillation","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T16:52:07.925279Z"},"links":{"cited_paper":"/paper/2301.03949","citing_paper":"/paper/2512.11654"},"observation_digest":"sha256:79ebde23dcdb0d699215a4484fd9ec210e6cc657dad144090922cd46d7669d57","observation_id":"d5580730-8254-426a-b930-c1d5389ddc69","resolution":{"observed_at":"2026-08-03T16:52:07.925279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2301.03949/citation-record","integrity":"/paper/2301.03949/integrity","json":"/paper/2301.03949/citation-record.json","paper":"/paper/2301.03949"},"outbound":[],"paper":{"arxiv_id":"2301.03949","last_updated":"2023-03-28T08:26:30Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T14:39:57.552494Z","submitted_at":"2023-01-10T13:15:42Z","title":"Modiff: Action-Conditioned 3D Motion Generation with Denoising Diffusion Probabilistic Models"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2301.03949."}