{"as_of":"2026-08-08T02:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:232a23a2cec1b683e9e42836dd21c9e73cdad277f21683b0c4b791878b9568b6","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":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:06:32.372579Z","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":"2026-07-03T14:08:22.368144Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-08-07T11:27:47.095844Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02452","last_updated":"2025-08-24T13:14:45Z","snapshot_observed_at":"2026-08-08T00:30:58.087521Z","submitted_at":"2025-06-03T05:17:37Z","title":"ANT: Adaptive Neural Temporal-Aware Text-to-Motion Model","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T11:27:47.095844Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2506.02452"},"observation_digest":"sha256:554b42cf95c024909bf09ead9b1415dbd838536a6d8eee4ffa71e24c2895e8de","observation_id":"5630dc34-1457-4cff-b5fe-ac97acce9f73","resolution":{"observed_at":"2026-08-07T11:27:47.095844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-08-07T12:06:32.372579Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03191","last_updated":"2025-05-31T11:02:24Z","snapshot_observed_at":"2026-08-07T12:01:41.223719Z","submitted_at":"2025-05-31T11:02:24Z","title":"Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward","version":1},"reference_index":120,"source":"pdf_text","source_observed_at":"2026-08-07T12:06:32.372579Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2506.03191"},"observation_digest":"sha256:a4da614402db3ca23df337ca2cd6b1fa303d98a223df180f13c68990dbe40ecd","observation_id":"f2456dae-e1a8-48cb-84ef-eb3baf17c3dc","resolution":{"observed_at":"2026-08-07T12:06:32.372579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-08-06T19:05:14.872481Z","title":"Momask: Generative masked modeling of 3d human motions,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.06590","last_updated":"2025-07-09T06:51:36Z","snapshot_observed_at":"2026-08-06T18:57:13.941090Z","submitted_at":"2025-07-09T06:51:36Z","title":"MOST: Motion Diffusion Model for Rare Text via Temporal Clip Banzhaf Interaction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:05:14.872481Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2507.06590"},"observation_digest":"sha256:8276fbae17c9cc0b207546472ae370647a365442ff54c8558b19d66bfa75f04b","observation_id":"5c8891ef-98e6-400a-9522-84f5a66999b2","resolution":{"observed_at":"2026-08-06T19:05:14.872481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-08-06T13:47:51.314668Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.20220","last_updated":"2025-07-27T10:59:29Z","snapshot_observed_at":"2026-08-06T13:47:31.254755Z","submitted_at":"2025-07-27T10:59:29Z","title":"Motion-example-controlled Co-speech Gesture Generation Leveraging Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:47:51.314668Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2507.20220"},"observation_digest":"sha256:bff8d112e2d520345d5377c4527af8b7ee76a7898c7d64eea1262af35a079053","observation_id":"33f9e589-4b05-4520-b643-b3e6db8c5f85","resolution":{"observed_at":"2026-08-06T13:47:51.314668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":"2312.00063","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-07-03T14:08:22.368144Z","title":"Momask: Generative masked modeling of 3d human motions","venue":null,"work_id":"a17618a8-4a10-4083-a411-c126d462a939","year":2023},"citing_paper":{"arxiv_id":"2605.14417","last_updated":"2026-05-20T06:15:55Z","snapshot_observed_at":"2026-07-06T23:25:49.545418Z","submitted_at":"2026-05-14T06:05:24Z","title":"Before the Body Moves: Learning Anticipatory Joint Intent for Language-Conditioned Humanoid Control","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-15T02:15:06.053570Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2605.14417"},"observation_digest":"sha256:f68891d0fd65e45f7fffe9cd5a5fa4f838fbff89506415b6648380dc9efe9592","observation_id":"41424468-9fba-43e5-a951-f0ac0df76b9f","resolution":{"observed_at":"2026-05-15T02:18:31.203500Z","resolver_source":"arxiv_id","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":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":"2312.00063","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-07-03T14:08:22.368144Z","title":"Momask: Generative masked modeling of 3d human motions","venue":null,"work_id":"a17618a8-4a10-4083-a411-c126d462a939","year":2023},"citing_paper":{"arxiv_id":"2605.14417","last_updated":"2026-05-20T06:15:55Z","snapshot_observed_at":"2026-07-06T23:25:49.545418Z","submitted_at":"2026-05-14T06:05:24Z","title":"Before the Body Moves: Learning Anticipatory Joint Intent for Language-Conditioned Humanoid Control","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-21T09:07:49.074474Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2605.14417"},"observation_digest":"sha256:06da3a9935c1a7a430395db95a56517436492207dc07f0ab2ea2be6efd2907ac","observation_id":"7ace25de-8f67-4d98-98d3-46383c7c424f","resolution":{"observed_at":"2026-05-21T09:09:56.113036Z","resolver_source":"arxiv_id","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":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":"2312.00063","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-07-03T14:08:22.368144Z","title":"Momask: Generative masked modeling of 3d human motions","venue":null,"work_id":"a17618a8-4a10-4083-a411-c126d462a939","year":2023},"citing_paper":{"arxiv_id":"2605.20649","last_updated":"2026-05-20T03:09:45Z","snapshot_observed_at":"2026-08-04T03:27:22.737171Z","submitted_at":"2026-05-20T03:09:45Z","title":"AMAR: Lightweight Attention-Based Multi-User Activity Recognition from Wi-Fi CSI","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-21T03:11:44.222945Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2605.20649"},"observation_digest":"sha256:2c34ef37747a79c46e11276f6e386b4f095b7dbac4ee2a8137eb3757ce65fede","observation_id":"a281ab36-d091-48e4-a0d1-11eba11ff53e","resolution":{"observed_at":"2026-05-21T03:13:56.117901Z","resolver_source":"arxiv_id","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":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":"2312.00063","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-07-03T14:08:22.368144Z","title":"Momask: Generative masked modeling of 3d human motions","venue":null,"work_id":"a17618a8-4a10-4083-a411-c126d462a939","year":2023},"citing_paper":{"arxiv_id":"2606.13364","last_updated":"2026-06-11T13:49:23Z","snapshot_observed_at":"2026-07-06T23:52:09.853158Z","submitted_at":"2026-06-11T13:49:23Z","title":"VideoMDM: Towards 3D Human Motion Generation From 2D Supervision","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T07:10:42.987128Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2606.13364"},"observation_digest":"sha256:5fdbf5e791f4d947dd355eed227bac50409c69f2228db304be4c41310079b286","observation_id":"9265749b-2f58-4781-93b6-bd7516721459","resolution":{"observed_at":"2026-07-03T14:08:22.370067Z","resolver_source":"arxiv_id","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":"2312.00063","last_updated":"2023-11-29T19:04:10Z","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00063","snapshot_observed_at":"2026-07-14T12:54:34.093482Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.10287","last_updated":"2026-07-11T12:33:20Z","snapshot_observed_at":"2026-08-07T03:37:48.852131Z","submitted_at":"2026-07-11T12:33:20Z","title":"InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-14T12:54:34.093482Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2607.10287"},"observation_digest":"sha256:35b5769630c55b2c66ccb4a6e70070e8d96c8c9ed3d6e08748d166952b41f7ed","observation_id":"703df403-11bf-43f7-a964-4521529e6c96","resolution":{"observed_at":"2026-07-14T12:54:34.093482Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2312.00063/citation-record","integrity":"/paper/2312.00063/integrity","json":"/paper/2312.00063/citation-record.json","paper":"/paper/2312.00063"},"outbound":[],"paper":{"arxiv_id":"2312.00063","last_updated":"2023-11-29T19:04:10Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T16:55:17.192399Z","submitted_at":"2023-11-29T19:04:10Z","title":"MoMask: Generative Masked Modeling of 3D Human Motions"},"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 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2312.00063."}