{"as_of":"2026-08-10T15:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8ace4d50a6f13cdb6b772ff9141c21d54025fd3305d6e0615707f6276b271102","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T22:44:28.998682Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2501.18726/citation-record","integrity":"/paper/2501.18726/integrity","json":"/paper/2501.18726/citation-record.json","paper":"/paper/2501.18726"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:44:29.303040Z","title":"Language2pose: Natural language grounded pose forecasting","venue":null,"work_id":"8f5cc902-096e-41d6-a9fe-9da2fd2cc2ef","year":2019},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.894409Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:bdeb9c89e4662f4769f39c6ef406dc6318de287463b310c316a2da34d74b67ac","observation_id":"14a2b0ec-7c88-4e8d-9721-0054b1f9a044","resolution":{"observed_at":"2026-08-09T22:44:29.307162Z","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":"2026-08-09T22:44:29.291739Z","title":"Hp-gan: Probabilistic3dhumanmotionprediction viagan","venue":null,"work_id":"4764684b-84dd-4a1c-901e-8dc179ce1d49","year":2018},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.898989Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:dd65aae85bb4fd62e7b7f5d971a12369c53151139a7bc6e3efd08d9febb6aa15","observation_id":"d1e43a77-c7ec-48c1-aec5-a47ee09d1b6d","resolution":{"observed_at":"2026-08-09T22:44:29.295575Z","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":"2026-08-09T22:44:29.281209Z","title":"Executingyour commands via motion diffusion in latent space","venue":null,"work_id":"ee02bef1-bc4b-4c32-80e9-d1d4d36d0c7b","year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.903042Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:f43f1eb2fa38eb2a7680521b4914dde2f6f34ec274cb196436b6bfd6fbdc93bb","observation_id":"77ed8563-7048-4c53-bd49-e1b5fe6cfba1","resolution":{"observed_at":"2026-08-09T22:44:29.284880Z","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":"2307.08691","last_updated":"2023-07-17T17:50:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-17T17:50:36Z","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08691","snapshot_observed_at":"2026-08-09T22:44:28.907049Z","title":"Flashattention-2: Faster attention with better parallelism and work partitioning.arXiv preprint arXiv:2307.08691, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.907049Z"},"links":{"cited_paper":"/paper/2307.08691","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:b340031da7055c3cb940bebcafd8e6f615720aea8c8e72bea9839a86775a5e90","observation_id":"2e5a3e74-9c11-4a78-9cb9-2a1ab9ae2c01","resolution":{"observed_at":"2026-08-09T22:44:28.907049Z","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":"2026-08-09T22:44:28.911208Z","title":"Flashattention: Fast and memory-efficient exact attention with io-awareness.Advances in Neural Information Processing Systems, 35:16344–16359, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.911208Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:83d6494c555309906bb9738463e5b98a100b3874557e21fe12325de31e7327ac","observation_id":"80779dcb-f547-4d65-bf0e-eb7512fab990","resolution":{"observed_at":"2026-08-09T22:44:28.911208Z","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":"2026-08-09T22:44:28.915601Z","title":"Diffusion models beat gans on image synthesis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.915601Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:97659ef37f0030f235609cf0e8bc54e038136124c55a54627dbf9f82c18766f2","observation_id":"5ee1ae47-de23-4a6f-bc4c-c11bea4fd603","resolution":{"observed_at":"2026-08-09T22:44:28.915601Z","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":"2026-08-09T22:44:29.257107Z","title":"Tm2d: Bimodality driven 3d dance generation via music-text integration","venue":null,"work_id":"3f7bdaee-b2f1-4c2d-b749-fb625237a2c7","year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.919972Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:5a0f65d2deae4191f133a23906e8a8e7036029f5f0cb9e1ceb330d3d0266e71e","observation_id":"6ae79813-3370-45cd-86d7-8e73eee074fb","resolution":{"observed_at":"2026-08-09T22:44:29.261154Z","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":"2026-08-09T22:44:28.923471Z","title":"Generative adversarial networks.Communications of the ACM, 63(11):139–144, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.923471Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:f650161a9607d4aa6cd57229758ca826b01663ff6d2d4448956ea433b6eaedac","observation_id":"a4851aec-5847-449d-817c-ca514f97ee7b","resolution":{"observed_at":"2026-08-09T22:44:28.923471Z","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":"2026-08-09T22:44:29.239741Z","title":"Improvedtrainingofwassersteingans","venue":null,"work_id":"8d534186-f2af-406e-849f-f834802d1ca9","year":2017},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.927396Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:a08a86777c83dc9b5c040bab620f7b326b2f08fdb3272a71b41f6e11ccdfe7d5","observation_id":"6cf0b76c-af75-4bd4-9712-6f5ebccf32dd","resolution":{"observed_at":"2026-08-09T22:44:29.243527Z","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":"2026-08-09T22:44:28.931344Z","title":"Generating diverse and natural 3d human motions from text","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.931344Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:8ba2ebd8f0ae276999c42c3b0d159d18c55bbf56aeebdb7c82d419593464b8f1","observation_id":"63553b81-280b-40b4-bae5-7809be0fc905","resolution":{"observed_at":"2026-08-09T22:44:28.931344Z","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":"2026-08-09T22:44:28.935137Z","title":"Momask: Generative masked modeling of 3d human motions.arXiv preprint arXiv:2312.00063, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.935137Z"},"links":{"cited_paper":"/paper/2312.00063","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:5d04af755fc2d3e02515e71d34b003353a5b7c831b019d7d601fa211398cdcec","observation_id":"8b035dc0-2e89-4df7-969a-f5736874761a","resolution":{"observed_at":"2026-08-09T22:44:28.935137Z","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":"2026-08-09T22:44:29.221777Z","title":"Robust motion in-betweening","venue":null,"work_id":"8ea45364-6fc3-4902-bdfe-dc8bbff1331a","year":2020},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.939244Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:28d99fd5cba302dac250094992a64bfd894e6d1cdf3613325adab5acc644d388","observation_id":"ee386a64-fedd-4877-862d-0b429d6c1a9c","resolution":{"observed_at":"2026-08-09T22:44:29.225533Z","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":"2026-08-09T22:44:28.942966Z","title":"Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.942966Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:b41d4ecf9a9e574caf0108169a23d9df0b58451f05d05ad23b1956800218d9b8","observation_id":"3ac8c8d1-1dc6-498d-b3bb-ef6e161543fd","resolution":{"observed_at":"2026-08-09T22:44:28.942966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.10652","last_updated":"2018-05-18T16:52:24Z","snapshot_observed_at":"2026-07-06T06:35:55.592795Z","submitted_at":"2018-04-27T19:13:34Z","title":"Human Motion Modeling using DVGANs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.10652","snapshot_observed_at":"2026-08-09T22:44:28.946713Z","title":"Human motion modeling using dvgans","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.946713Z"},"links":{"cited_paper":"/paper/1804.10652","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:c8ee0cd8652301b96e779a0ee18e6aa6eb62727fd41e74a8cb552cb18a6a958b","observation_id":"f2efc9a3-3062-4955-a256-ed4951ca4aa1","resolution":{"observed_at":"2026-08-09T22:44:28.946713Z","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":"2026-08-09T22:44:28.950508Z","title":"Improved denoising diffusion probabilistic models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.950508Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:142ac336fa061c1186d2e4749636d3dcc4f9814adc1bebd0111434bd8ba229a4","observation_id":"46cb6aa2-c8a9-438d-954e-822e753da666","resolution":{"observed_at":"2026-08-09T22:44:28.950508Z","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":"2026-08-09T22:44:29.197275Z","title":"Temos: Generatingdiversehumanmotionsfrom textual descriptions","venue":null,"work_id":"54c4fea0-a0d0-493d-b944-acc37729a7ff","year":2022},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.953790Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:17870cd49af92d6d5d310ac70766c555907febf492f806f43a75d6e1f5234358","observation_id":"21358d0f-1343-48bd-afbe-e6abaa3deab0","resolution":{"observed_at":"2026-08-09T22:44:29.201211Z","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":"2312.03596","last_updated":"2024-03-28T03:26:51Z","snapshot_observed_at":"2026-07-06T16:57:46.724781Z","submitted_at":"2023-12-06T16:35:59Z","title":"MMM: Generative Masked Motion Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03596","snapshot_observed_at":"2026-08-09T22:44:28.956992Z","title":"Mmm: Generative masked motion model.arXiv preprint arXiv:2312.03596, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.956992Z"},"links":{"cited_paper":"/paper/2312.03596","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:487ea3a512a981c65a1af8932ee5ce490fde47fbb277d690e9be4917705894e3","observation_id":"2dda23d6-53e6-46c5-bbe2-cf4be130cca7","resolution":{"observed_at":"2026-08-09T22:44:28.956992Z","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":"2026-08-09T22:44:28.960445Z","title":"Generating diverse high-fidelity images with vq-vae-2","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.960445Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:67e2391d68731d4c4c5809295ab15b6e27d90ea77f94187a5d5cdedfeb764f6a","observation_id":"66f084bc-9e48-47c2-9a6d-d5e39252c85d","resolution":{"observed_at":"2026-08-09T22:44:28.960445Z","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":"2026-08-09T22:44:28.963589Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.963589Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:ea8759078c621dad6ad1a84e3de3a38eb1db03da97ad7f52766239b7a91a5d6b","observation_id":"56dfed1a-f759-4fb8-adbe-4ff712e89ae1","resolution":{"observed_at":"2026-08-09T22:44:28.963589Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-09T22:44:28.966626Z","title":"Denoising diffusion implicit models.arXiv preprint arXiv:2010.02502, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.966626Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:dda20fa9abd280ac8b9db23ba634e40d5502d1f78f39f1f1bd73e363056b5770","observation_id":"a97dd0b5-67db-4810-b964-beef1e15022d","resolution":{"observed_at":"2026-08-09T22:44:28.966626Z","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":"2026-08-09T22:44:28.970031Z","title":"Motionclip: Exposing human motion generation to clip space","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.970031Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:c0a5877f6cd326bffa8f951d25b572598e6e83066e4bccddf9efb5e187df2ea6","observation_id":"94304d35-aa8b-48f0-913c-a4a08c2d868d","resolution":{"observed_at":"2026-08-09T22:44:28.970031Z","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":"2026-08-09T22:44:28.973505Z","title":"Human motion diffusion model.arXiv preprint arXiv:2209.14916, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.973505Z"},"links":{"cited_paper":"/paper/2209.14916","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:4da25052c0eec414ab5a04626194703f23216d4b7a4ac57803e0dfd8452b9739","observation_id":"3dd51322-86ad-404b-814f-038de532a1d2","resolution":{"observed_at":"2026-08-09T22:44:28.973505Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06635","last_updated":"2024-08-27T01:27:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-11T18:51:59Z","title":"Gated Linear Attention Transformers with Hardware-Efficient Training","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.06635","snapshot_observed_at":"2026-08-09T22:44:28.977442Z","title":"Gatedlinearattention transformers with hardware-efficient training.arXiv preprint arXiv:2312.06635, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.977442Z"},"links":{"cited_paper":"/paper/2312.06635","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:c5477a8274e081a3d3cbaa33595cc330d8a809fbd0bfbb7a3ad7ba27db06ac4c","observation_id":"aada5b96-0e7e-47d3-a894-56029f72f887","resolution":{"observed_at":"2026-08-09T22:44:28.977442Z","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":"2026-08-09T22:44:29.166083Z","title":"Motiondiffuse: Text-driven human motion generation with diffusion model.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024","venue":null,"work_id":"39f724ad-a20b-4a3d-ab90-69d751412249","year":2024},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.981046Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:ba9e30bbb75530c0586535e9f70f0f48ef7ad6c33a257839ff52fe7df63d5812","observation_id":"4c192aa8-8a44-4b1f-af3a-b450618afbad","resolution":{"observed_at":"2026-08-09T22:44:29.170524Z","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":"2501.12832","last_updated":"2025-01-22T12:19:47Z","snapshot_observed_at":"2026-08-06T07:28:30.100317Z","submitted_at":"2025-01-22T12:19:47Z","title":"FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image Restoration","version":1},"cited_work":{"arxiv_id":"2501.12832","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.12832","snapshot_observed_at":"2026-08-09T22:44:29.054876Z","title":"FDG-Diff: Frequency-Domain-Guided Diffusion Framework for Compressed Hazy Image Restoration","venue":"eess.IV","work_id":"8cbc5744-a3cc-42e2-af93-b169636b95ad","year":2025},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.984363Z"},"links":{"cited_paper":"/paper/2501.12832","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:22bafd502450ddc6ca0960d583f0631865857ae070712d731ea0eda754ea0c0f","observation_id":"9092a34f-2d25-4558-a5bb-695f6df50c66","resolution":{"observed_at":"2026-08-09T22:44:29.061206Z","resolver_source":"local_arxiv","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":"2411.06481","last_updated":"2025-04-16T16:45:12Z","snapshot_observed_at":"2026-08-02T08:20:46.856115Z","submitted_at":"2024-11-10T14:41:38Z","title":"KMM: Key Frame Mask Mamba for Extended Motion Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.06481","snapshot_observed_at":"2026-08-09T22:44:28.988014Z","title":"Kmm: Keyframemaskmambaforextendedmotiongeneration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.988014Z"},"links":{"cited_paper":"/paper/2411.06481","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:0eeefcc55da9d50baff2d5724f91532b6518fc08a568cdefbc5fe1e665e90187","observation_id":"1165d2bd-44e2-493f-b55f-7ea4f708b098","resolution":{"observed_at":"2026-08-09T22:44:28.988014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10061","last_updated":"2024-07-14T03:12:19Z","snapshot_observed_at":"2026-08-03T17:31:24.474732Z","submitted_at":"2024-07-14T03:12:19Z","title":"InfiniMotion: Mamba Boosts Memory in Transformer for Arbitrary Long Motion Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10061","snapshot_observed_at":"2026-08-09T22:44:28.991461Z","title":"Infinimotion: Mamba boosts memory in transformer for arbitrary long motion generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.991461Z"},"links":{"cited_paper":"/paper/2407.10061","citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:4e95058e73d70930d5a6e99e3328337a386aad55e4443ac3299c16940fbcece1","observation_id":"1eb5c156-89ba-4862-b551-3655d106f92b","resolution":{"observed_at":"2026-08-09T22:44:28.991461Z","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":"2026-08-09T22:44:29.155421Z","title":"Motionmamba: Efficient and long sequence motion generation","venue":null,"work_id":"c7686dee-6ee4-44e1-924d-124abd5aa003","year":2025},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.995200Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:40e453d859b403892d943fbc4bc9a7dd9ebe9d485b15f73d197003c635dd14d9","observation_id":"d5be8908-ffbd-4351-bbcc-38cf41048c9e","resolution":{"observed_at":"2026-08-09T22:44:29.159142Z","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":"2026-08-09T22:44:29.144265Z","title":"Attt2m: Text-driven human motion generation with multi-perspective attention mechanism","venue":null,"work_id":"4eb6123c-76f8-4d60-89d7-b72527f7f4ef","year":2023},"citing_paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T22:44:28.998682Z"},"links":{"citing_paper":"/paper/2501.18726"},"observation_digest":"sha256:32fb5600963dd79aad1c7e0b17c482d4d77d8b2c482edcf2d38358c6d0ead796","observation_id":"09d36c0e-d623-46d9-92bd-11d4c7a16de1","resolution":{"observed_at":"2026-08-09T22:44:29.148296Z","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"}}],"paper":{"arxiv_id":"2501.18726","last_updated":"2025-01-30T20:06:30Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T22:39:55.351266Z","submitted_at":"2025-01-30T20:06:30Z","title":"Strong and Controllable 3D Motion Generation"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":10},"total_outbound_references":29},"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 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2501.18726."}