{"as_of":"2026-08-10T15:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ff6627e19b38bcade111845c36e7df3523c06013dfb9b367a351c8b5a804be46","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:03:03.903769Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-03T13:08:06.676197Z","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":"2026-05-16T13:47:57.521926Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"cited_work":{"arxiv_id":"2507.19850","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.19850","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Finemotion: A dataset and benchmark with both spatial and temporal annotation for fine-grained motion generation and editing","venue":null,"work_id":"dd72b51a-c745-4c63-9402-1008163a8d28","year":2025},"citing_paper":{"arxiv_id":"2601.10632","last_updated":"2026-04-10T16:10:59Z","snapshot_observed_at":"2026-07-06T22:41:48.115083Z","submitted_at":"2026-01-15T17:52:29Z","title":"CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-05-16T13:43:26.460480Z"},"links":{"cited_paper":"/paper/2507.19850","citing_paper":"/paper/2601.10632"},"observation_digest":"sha256:538c7c16ba3de96adb83d1b16f7b95c34189edd46eeca1e271077f853d64bfcf","observation_id":"359566cd-06fc-4c07-9aa3-89c491199c64","resolution":{"observed_at":"2026-05-16T13:47:57.523674Z","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":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.19850","snapshot_observed_at":"2026-08-03T13:08:06.676197Z","title":": FineMotion : A dataset and benchmark with both spatial and temporal annotation for fine-grained motion generation and editing","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29133","last_updated":"2026-07-31T08:04:32Z","snapshot_observed_at":"2026-08-08T03:05:06.510543Z","submitted_at":"2026-07-31T08:04:32Z","title":"Interactive Generative Motion Editing via Scheduled Inpainting","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-03T13:08:06.676197Z"},"links":{"cited_paper":"/paper/2507.19850","citing_paper":"/paper/2607.29133"},"observation_digest":"sha256:4590a85296a2ad663d0b39f9b2537d2eb10c283a3f6d1cb65360e3f11e77fe14","observation_id":"a0d07012-881d-4492-9dea-f68c7d7b03a3","resolution":{"observed_at":"2026-08-03T13:08:06.676197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.19850/citation-record","integrity":"/paper/2507.19850/integrity","json":"/paper/2507.19850/citation-record.json","paper":"/paper/2507.19850"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.984638Z","title":"Sinc: Spatial composition of 3d human motions for simultaneous action generation supplementary material","venue":null,"work_id":"803fbbbd-15f6-4218-aaa4-ba3c69eed1e4","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T14:02:59.717925Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:7fb5d4273b6a75a699f55e7ecf62aacc50e2fe2dfda319512a635c936354d2d3","observation_id":"b1aa249a-c89a-4327-ace0-3e89fddc566c","resolution":{"observed_at":"2026-08-06T14:03:08.989032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.971086Z","title":"Posescript: 3d human poses from natural language","venue":null,"work_id":"e93dba0d-e506-490f-8d84-c081ae67df7a","year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T14:02:59.807045Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:fc2f44f41bb57e0eed5d15d41f04ed27fb69d43967ac9ecae5e38e04ce08db3b","observation_id":"3b3cd341-549c-46e1-85ae-1121f0ae21ba","resolution":{"observed_at":"2026-08-06T14:03:08.975112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.957299Z","title":"Posefix: Correcting 3d hu- man poses with natural language","venue":null,"work_id":"dc5bfcb9-45ee-4d4c-95c1-95e2e328c8ba","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T14:02:59.914336Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:0947c66aa626a949104deb8bed2085711cb5aaf8e2d9762541e754874e067568","observation_id":"4a9f523f-8590-4b48-8751-93f9d961fb5d","resolution":{"observed_at":"2026-08-06T14:03:08.961409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.942668Z","title":"https://www.grammarly.com","venue":null,"work_id":"bfb6aaaf-6a7b-46a3-a4ae-30213a6e3098","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.034244Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:f7fdd437f6894ea7bccc92147faa7f5a09917ffcd2b530c453f917320b36e135","observation_id":"57d2267d-e2df-4de2-9547-81a0940ab4c6","resolution":{"observed_at":"2026-08-06T14:03:08.947119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.928454Z","title":"Ac- tion2motion: Conditioned generation of 3d human motions","venue":null,"work_id":"fb5a1714-b6dc-497c-b7d4-1417883e70a6","year":2021},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.100950Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:502de205b68e09f6fedbfb5a071a06eecd0f562a12fcf91cc7d74c2f56d17009","observation_id":"4ab8f3f7-20d5-4f2a-a4b9-ac55cc8ae384","resolution":{"observed_at":"2026-08-06T14:03:08.933051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.913771Z","title":"Generating diverse and natural 3d human motions from text","venue":null,"work_id":"5d590831-1f6a-476d-8953-d514e5f7273d","year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.207743Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:f2ec3cc26052622ebfafb5569c4c6bb0f75d006fe7b7705bebed274464291da4","observation_id":"159a3a8a-ff06-4a23-96a6-cc9d897b7365","resolution":{"observed_at":"2026-08-06T14:03:08.918502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.898671Z","title":"Tm2t: Stochastic and tokenized modeling for the reciprocal genera- tion of 3d human motions and texts","venue":null,"work_id":"679b84b3-82e6-4645-9eea-1612bc76a97a","year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.323317Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:fc679e08ac3e64ac4abe4078e6b5f873b75cb41b0ac6299eea96363f85800e28","observation_id":"66d3f693-bd5f-4e7f-aa44-93bd432f7eec","resolution":{"observed_at":"2026-08-06T14:03:08.904119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.883421Z","title":"Momask: Generative masked model- ing of 3d human motions","venue":null,"work_id":"1fb39236-948f-4eb9-bc8b-968a8aafa9ca","year":1900},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.400645Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:b4a0219d39201aaca89b476f66ce7cbea491ddddc884f6500f2757a293bd34c0","observation_id":"f136fbc2-7a7b-4ef5-9830-e3605064f659","resolution":{"observed_at":"2026-08-06T14:03:08.888782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2310.20323","last_updated":"2023-11-28T06:18:33Z","snapshot_observed_at":"2026-07-06T16:41:03.157136Z","submitted_at":"2023-10-31T09:58:11Z","title":"SemanticBoost: Elevating Motion Generation with Augmented Textual Cues","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.20323","snapshot_observed_at":"2026-08-06T14:03:00.467913Z","title":"Semanticboost: Elevating motion generation with augmented textual cues","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.467913Z"},"links":{"cited_paper":"/paper/2310.20323","citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:88b341bbc9ebd86345cefb4454651ccc804e12fbd4b8e032ab37ccd30b39da51","observation_id":"0bcf694c-6527-41f8-8b92-134056b67200","resolution":{"observed_at":"2026-08-06T14:03:00.467913Z","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":"2026-08-06T14:03:08.867747Z","title":"Motiongpt: Human motion as a foreign language","venue":null,"work_id":"e5971438-5f84-40dd-b0eb-9a297e7e0edb","year":2024},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.534183Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:00585e8180310bff28f4400c382cb6382bac26c8e6cc713e6b7d5bf5188a3b80","observation_id":"77055eb9-2e15-4164-bb7b-4e6f5e3a168b","resolution":{"observed_at":"2026-08-06T14:03:08.872670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.850862Z","title":"Action-gpt: Leveraging large-scale language models for improved and generalized action gen- eration","venue":null,"work_id":"0b1ffbe8-2b3f-466c-8250-1c94708ebbff","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.631544Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:84e3fc693807fc2b2bf4459bc630bd68b6179fc60026049060febf6419d563d9","observation_id":"a9130912-39e5-43fe-b76f-a60d7574a083","resolution":{"observed_at":"2026-08-06T14:03:08.856475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.834106Z","title":"Flame: Free- form language-based motion synthesis & editing","venue":null,"work_id":"0f100c04-a1ae-46f0-8e81-9299f4dc8457","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.766757Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:3eab2095519849038c3f95f71c700088ab4dea10a883da197b143d9205e0d638","observation_id":"7f57d9bc-a692-42fa-afb2-5a13e089910c","resolution":{"observed_at":"2026-08-06T14:03:08.839035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.667784Z","title":"Dance- former: Music conditioned 3d dance generation with para- metric motion transformer","venue":null,"work_id":"58760480-f22c-4e22-9652-ee7ac12d2efd","year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.810120Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:0dd8466d1a5cb3ad5e0e5e262f2825e0b19d0325ede17ed02e17a43c8621572f","observation_id":"3926c348-8b61-4fa9-9924-037b0e106032","resolution":{"observed_at":"2026-08-06T14:03:08.796583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2401.01382","last_updated":"2024-01-01T09:25:20Z","snapshot_observed_at":"2026-08-05T11:59:16.015158Z","submitted_at":"2024-01-01T09:25:20Z","title":"Exploring Multi-Modal Control in Music-Driven Dance Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.01382","snapshot_observed_at":"2026-08-06T14:03:00.910248Z","title":"Exploring multi-modal control in music- driven dance generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.910248Z"},"links":{"cited_paper":"/paper/2401.01382","citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:7e259de664831e8c5d53e019ebb8687441398e45556b702ce0146a0abbbef225","observation_id":"90b852a6-1f6e-46ea-8809-9d32500ca27f","resolution":{"observed_at":"2026-08-06T14:03:00.910248Z","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":"2026-08-06T14:03:08.320124Z","title":"Smpl: A skinned multi- person linear model","venue":null,"work_id":"bad10dc1-b6f5-476b-9211-03a02d1ffa38","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:00.991765Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:d2f6ba43c7be3745102d5f7a830728b1e392e73bfe6e963fa5198fd033b28628","observation_id":"0e298b33-6ea8-40bc-b0da-63cd7a62c30d","resolution":{"observed_at":"2026-08-06T14:03:08.537911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:08.045285Z","title":"Amass: Archive of motion capture as surface shapes","venue":null,"work_id":"2a5aecae-41ae-44b7-88f7-ba5219a56d40","year":2019},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.007072Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:e98d7845845d669b8537ca4f9750b66fc798574f58e2a15fb43e9e082c4d38db","observation_id":"c4c6ea66-a84b-4576-a70d-04bdf813e8d7","resolution":{"observed_at":"2026-08-06T14:03:08.165972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:07.784335Z","title":"Action- conditioned 3d human motion synthesis with transformer vae","venue":null,"work_id":"bae33134-200a-4bb9-8880-a3e4d2e77d56","year":2021},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.076289Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:5fabd6f74d05d3b7f1349839371d44637872d0d9998afa5e0d5eae06e3f02411","observation_id":"2e8fef04-c274-4fc6-b9ea-e3b4029f81e7","resolution":{"observed_at":"2026-08-06T14:03:07.882962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:01.118478Z","title":"Temos: Generating diverse human motions from textual descriptions","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.118478Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:0beb64e52808353d638e5103b0107e187b5c284745ac0c272078b555c4a8ded1","observation_id":"b8dca4d8-5a53-4a05-bff7-683861857d38","resolution":{"observed_at":"2026-08-06T14:03:01.118478Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:01.223067Z","title":"The kit motion-language dataset","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.223067Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:c7e6f9df65885b0ac7fd6d6dacd2bdf4d85b6b7706165a373f963bba8cf3ea60","observation_id":"9cb210cd-0827-492c-a317-1cc89e6b0191","resolution":{"observed_at":"2026-08-06T14:03:01.223067Z","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":"2026-08-06T14:03:07.196387Z","title":"Modi: Un- conditional motion synthesis from diverse data","venue":null,"work_id":"374d50b4-0ed7-4ed4-92f0-5b390b96f688","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.332033Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:8b5864c8f37a140db70fec36e6ed4cec56467d048ffa463cb0a66ebde8a8f7b4","observation_id":"049cc3ff-0204-49a6-8582-b0b9c5130d12","resolution":{"observed_at":"2026-08-06T14:03:07.319116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:07.074737Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"e15dbb33-be0b-4361-b231-5f6a92a6a1ea","year":2021},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.430567Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:8217029630080227fc857727466364f776bccfefddbc55a7fa74760a4aadb4f7","observation_id":"939d2f9b-d0bf-403f-87d5-6708c63fb9aa","resolution":{"observed_at":"2026-08-06T14:03:07.185798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:06.906344Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer","venue":null,"work_id":"8b6ea37c-0eac-461d-b620-b2c37a091b2d","year":2020},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.537208Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:9a0c4665528b1ad19e26340927dc7857b4b7da2b17a10dc632dd5fbc035da242","observation_id":"54719c5b-6be9-4670-8d44-04ec64b70224","resolution":{"observed_at":"2026-08-06T14:03:06.974344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-06T14:03:01.609376Z","title":"Gemini: a family of highly capable multimodal models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.609376Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:1d15883e5cb440b7aee4111152dad350ad7d30df599abdeb093881b34e144a77","observation_id":"6e339890-6e23-4954-bcf8-4cef1374ae69","resolution":{"observed_at":"2026-08-06T14:03:01.609376Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:01.745330Z","title":"Motionclip: Exposing human motion generation to clip space","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.745330Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:db1f5a0d08b21ad71641629117171f16f29840b60bdd66247d42fec36b1df2d5","observation_id":"33e741eb-bf94-47aa-b708-f08a15eee562","resolution":{"observed_at":"2026-08-06T14:03:01.745330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14916","last_updated":"2022-10-03T09:17:41Z","snapshot_observed_at":"2026-07-06T13:57:50.746457Z","submitted_at":"2022-09-29T16:27:53Z","title":"Human Motion Diffusion Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14916","snapshot_observed_at":"2026-08-06T14:03:01.904759Z","title":"Human motion dif- fusion model","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.904759Z"},"links":{"cited_paper":"/paper/2209.14916","citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:9c0a60d9e1bc90c58ac2d110af2ae6012852de4bb9aeb5851016cc79c336917a","observation_id":"81398c11-8928-49a8-9d1e-3e654c2b1e9c","resolution":{"observed_at":"2026-08-06T14:03:01.904759Z","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":"2026-08-06T14:03:06.724161Z","title":"Edge: Editable dance generation from music","venue":null,"work_id":"82f08e20-c499-464a-845e-8487920d7977","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.015848Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:3a778390d3339c4fab568b9c31a1b340478efe08e0faa34a1a66bac385fc9454","observation_id":"eadb7ecc-65da-4374-b2ed-c8815f7c15e8","resolution":{"observed_at":"2026-08-06T14:03:06.805436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:02.118754Z","title":"Neural discrete representation learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.118754Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:7855e9b50a614107f7c602ffa803f512c0e8e3ebe3a8e9922ca627c851040076","observation_id":"cbd700f5-59ab-4b57-8e1c-2d6919dab81b","resolution":{"observed_at":"2026-08-06T14:03:02.118754Z","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":"2026-08-06T14:03:06.529609Z","title":"Fg-t2m: Fine-grained text-driven human motion generation via diffusion model","venue":null,"work_id":"0dbbdbc9-d08a-4ede-af25-80cd0ec81e78","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.231014Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:736b0818c56e4e7ca3a14e2cb6f99fec985d9f28cfe18028a384a7b3d0e2cf9e","observation_id":"5822ef97-1e0f-4a73-a420-16b944ec469b","resolution":{"observed_at":"2026-08-06T14:03:06.614296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:02.359054Z","title":"Motionscript: Natural language descriptions for expressive 3d human motions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.359054Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:cc225510a2a1047b428d8c2f935d0b3054def93b15a35624519014f1516666fe","observation_id":"fe9ae33c-94e2-45c7-9b2b-f893aeca1919","resolution":{"observed_at":"2026-08-06T14:03:02.359054Z","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":"2026-08-06T14:03:06.396233Z","title":"Generating human motion from textual descrip- tions with discrete representations","venue":null,"work_id":"9677e01a-1d5e-49e1-bcc7-052695cbbb11","year":2023},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.488839Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:5bf6bc720288255918834745d2da65ac23b4eba67da80dcd31670cad50d9c6b7","observation_id":"66d33c9f-eb12-4b01-b56c-8b1dd7ffd9d8","resolution":{"observed_at":"2026-08-06T14:03:06.467456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:06.259367Z","title":"Motiondif- fuse: Text-driven human motion generation with diffusion model","venue":null,"work_id":"37ec2e4a-494b-4f14-bcc0-66cf3bbacd79","year":2024},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.629747Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:c7f3243a3770087e828cc6bb7c57be6e8d8f2ff7e7fe70d1d99a947e80d61f2c","observation_id":"5110fd30-3132-49a7-bb4d-bca169603f5f","resolution":{"observed_at":"2026-08-06T14:03:06.302068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:06.133781Z","title":"Finemogen: Fine-grained spatio- temporal motion generation and editing","venue":null,"work_id":"8e7fe1cd-e261-4ea8-82ad-d23f2e5c9d81","year":2024},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.768321Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:bc9007d184287377a6af9ee1b98ee1b80d89abd7c15631ea88b5d9fc874b2d3d","observation_id":"a58ff25d-200d-4698-b21a-0bffcfdac259","resolution":{"observed_at":"2026-08-06T14:03:06.177638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"1904.09675","last_updated":"2020-02-24T18:59:28Z","snapshot_observed_at":"2026-07-29T15:42:51.774083Z","submitted_at":"2019-04-21T23:08:53Z","title":"BERTScore: Evaluating Text Generation with BERT","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.09675","snapshot_observed_at":"2026-08-06T14:03:02.870849Z","title":"Bertscore: Evaluating text genera- tion with bert","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.870849Z"},"links":{"cited_paper":"/paper/1904.09675","citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:462a5f1d9a6ba6f1d406ce4edf5e318cd1a9daec5f36c5ab70b9e4810e7cadb3","observation_id":"58a57cc7-3096-4082-824f-1e2057fd418e","resolution":{"observed_at":"2026-08-06T14:03:02.870849Z","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":"2026-08-06T14:03:06.028426Z","title":"Mo- tiongpt: Finetuned llms are general-purpose motion genera- tors","venue":null,"work_id":"e0c048d5-69b8-4a9c-98f8-941e947fcd45","year":2024},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:02.943255Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:ebdba85a0f7fec275f66f3da5ab7261807a5846ce5e289c0ea56386c021f90c3","observation_id":"f136c010-ab62-489c-a747-9eb319b9a155","resolution":{"observed_at":"2026-08-06T14:03:06.069977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:05.931338Z","title":"The textual descriptions in our FineMotion dataset are under the CC BY 4.0 International license","venue":null,"work_id":"eea9847c-7aeb-4be0-a5f6-ecebc06d207e","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.019242Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:764592e77692906fe9ed7a125c5a3afd5395d26d99ad4d42ef1f38e56d68314f","observation_id":"a0da3cdd-b3ca-45a7-b664-6688cf08a408","resolution":{"observed_at":"2026-08-06T14:03:05.990055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:05.785171Z","title":"As shown in Fig","venue":null,"work_id":"f303123c-50e3-4c5b-9d1f-72fcc4458efa","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.104569Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:5d5382f7583d865353ab068300e4d081036dfb6176257665b4256ec9c9a7cc9f","observation_id":"08331da1-09c4-40ca-9458-c564a0ca1611","resolution":{"observed_at":"2026-08-06T14:03:05.851296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:05.634247Z","title":"Then, he slightly turns his upper body to the right","venue":null,"work_id":"feea9449-1976-4771-a5e7-543068cecee7","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.174978Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:d741387bf9840c9f66debf676fa0b5e7beb374f1f0ef6da415c21be0ddb4e9fb","observation_id":"47333990-fcde-4cc2-bc59-757cd37cbd51","resolution":{"observed_at":"2026-08-06T14:03:05.708298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:05.450413Z","title":"9 and 10","venue":null,"work_id":"a82adfab-afd9-451a-912f-1d01218e1997","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.240894Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:993e4c0dbeb9450923ede94c01f57950f079cc4785f382ad2138c56ca8fc2d89","observation_id":"1bec6e37-d4f7-4bf5-853f-aac9a6d7906c","resolution":{"observed_at":"2026-08-06T14:03:05.534798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:05.268169Z","title":"• (T&DT)-MDM builds from MDM [25]","venue":null,"work_id":"f03d7e46-b7c7-4912-9f37-e49cefa8ea56","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.316371Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:19e345e1d8c93547798f519822013d02096b250b005c168b930a7591a7acdd3f","observation_id":"1e868609-9c7a-4977-97be-f80929d7a793","resolution":{"observed_at":"2026-08-06T14:03:05.345759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:05.112554Z","title":"Notably, since we replace the text encoder with that of T5, the dimension of output text embedding turns to 768 rather than that of the CLIP text encoder, 512","venue":null,"work_id":"069f3d07-4b04-430f-a611-e7888ecc8861","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.404603Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:2499a12b22f5d6968fb6b147c70a96425ea92e9e985f2a8edb4ec5703c7c331e","observation_id":"4521e058-4325-4761-aec7-21b43677fb64","resolution":{"observed_at":"2026-08-06T14:03:05.188164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:04.955778Z","title":"Fine-grained text captures detailed body part movements and timing, while coarse text supplements global motion semantics, both crucial for pre- cise motion generation","venue":null,"work_id":"94da2f8f-9437-4b79-a81b-5d548f60c654","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.485014Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:244daf721af10b0bdc2f97c297083741a6daba8aaee1fdb36bc3d7ff9b9114f3","observation_id":"7cefdcd9-fd96-452f-92ee-a7162b618082","resolution":{"observed_at":"2026-08-06T14:03:05.016841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:04.809493Z","title":null,"venue":null,"work_id":"c1c0c989-9019-4bdb-93a2-b031641aa7b9","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.565037Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:57c79f9ebf7df81a69fb4fa50786ff4f0a548e93b4f72389475dab0086f214e9","observation_id":"d102a668-113b-4b8a-bd1c-b148854a2248","resolution":{"observed_at":"2026-08-06T14:03:04.879140Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:04.652843Z","title":"Specifically, we de- note the strategy of connecting the coarse text (T) and de- tailed text (DT) into a single text and feeding it into the text encoder as ‘TDT’","venue":null,"work_id":"a339aa28-2e6e-4b22-b0ae-e836f63412e4","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.614506Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:ed19b84514ea578487a394227d0b0c75721d5df8fe2c1bf60a60ebb8d73e5939","observation_id":"53793f8d-8a08-4bb6-9523-ab90ef15a2ca","resolution":{"observed_at":"2026-08-06T14:03:04.709256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:04.468098Z","title":null,"venue":null,"work_id":"f98bcc31-32c2-416e-aa1b-56113dac467e","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.694421Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:5444327dcbf5b3f2d87f0c3c0338e6d674e191a4036149e5b84eb271a5d8d4bc","observation_id":"0fa536e6-1807-4ad9-847f-bfb5367c94c5","resolution":{"observed_at":"2026-08-06T14:03:04.557710Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:04.320779Z","title":"Consequently, future work will fo- cus on developing effective methods for spatial human mo- tion editing","venue":null,"work_id":"76925b5e-da33-41ae-8521-5c9fa3c1cd47","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.826303Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:d58b07ccab8103e39d9519c05608f63636d217db72b26a656908f4b25fc8b076","observation_id":"a074b59b-fa6c-40c8-862c-183fb8dfd4f0","resolution":{"observed_at":"2026-08-06T14:03:04.381269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:04.159908Z","title":"original text: a person lifts their left wrist towards their face as if to look at a watch editing requirement: Lift your left hand to the head","venue":null,"work_id":"31edc41c-ec43-4ff5-b315-ed321c1e3575","year":null},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:03.903769Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:c94b8d1671f84b5b7e92986554ca940bf02c2bbf814ee276c3ce0be391639707","observation_id":"6929302f-b980-45b5-931e-c9879741b32e","resolution":{"observed_at":"2026-08-06T14:03:04.252933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:03:07.496878Z","title":null,"venue":null,"work_id":"c62fcd44-9b9c-4239-a407-b41d8ca3b013","year":2022},"citing_paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing","version":1},"reference_index":497,"source":"pdf_text","source_observed_at":"2026-08-06T14:03:01.152842Z"},"links":{"citing_paper":"/paper/2507.19850"},"observation_digest":"sha256:31efd1b1395cfed1915dbe6bb4e475c94eead9569781b9568612d3b5529f661d","observation_id":"3cc71902-7d4c-4407-a636-fc120c52f656","resolution":{"observed_at":"2026-08-06T14:03:07.633272Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"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"}}],"paper":{"arxiv_id":"2507.19850","last_updated":"2025-07-26T07:54:29Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T08:10:19.194078Z","submitted_at":"2025-07-26T07:54:29Z","title":"FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":12,"verified_exact":0,"verified_fuzzy":34},"total_outbound_references":47},"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 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2507.19850."}