{"as_of":"2026-08-14T13:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:57120b1e04f9adb4a7523a88343e7b098a4d6b972d6a69e07eb3c0e5175a6516","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T23:16:11.265253Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:06:31.257017Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.01449","snapshot_observed_at":"2026-08-07T12:06:31.257017Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03191","last_updated":"2025-05-31T11:02:24Z","snapshot_observed_at":"2026-08-08T02:50:50.296059Z","submitted_at":"2025-05-31T11:02:24Z","title":"Multimodal Generative AI with Autoregressive LLMs for Human Motion Understanding and Generation: A Way Forward","version":1},"reference_index":108,"source":"pdf_text","source_observed_at":"2026-08-07T12:06:31.257017Z"},"links":{"cited_paper":"/paper/2501.01449","citing_paper":"/paper/2506.03191"},"observation_digest":"sha256:1465cdd08edcf3cc96c679b9427114f696276074b8af9970d9ae44192e100072","observation_id":"0fa42734-e00b-4e84-a1df-f5e0e320b105","resolution":{"observed_at":"2026-08-07T12:06:31.257017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2501.01449/citation-record","integrity":"/paper/2501.01449/integrity","json":"/paper/2501.01449/citation-record.json","paper":"/paper/2501.01449"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T23:16:12.054512Z","title":"Text2action: Generative adversarial synthesis from language to action","venue":null,"work_id":"aa56987a-a362-413a-89df-4b1a966e0253","year":2018},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.013600Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:044bb9f41ed77a752ea1d90004950410f0f84b34d2794a0742849bc26f09e18d","observation_id":"5cbde967-8bab-4ba9-98c1-3d232f559bde","resolution":{"observed_at":"2026-08-10T23:16:12.059417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:12.040910Z","title":"Lan- guage2pose: Natural language grounded pose forecasting","venue":null,"work_id":"b5e46836-1790-44a4-a402-0e6a99346270","year":2019},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.018986Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:1a228749008e7364803c7f15f1d0731b441ac13b3daaae6d5d629ed17cecc1ad","observation_id":"d6852584-fc00-458c-acef-732f153851cb","resolution":{"observed_at":"2026-08-10T23:16:12.045132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:12.027299Z","title":"Lan- guage2pose: Natural language grounded pose forecasting","venue":null,"work_id":"cd12db9e-f684-4f24-9caf-c728ecf34fc1","year":2019},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.024154Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:4d4bf4ff8768f9bdf41a6f392649f3444bb32a0e77d5e6f844b26417a3479760","observation_id":"ff188f66-11ef-4c0e-8faf-b3d5f5e04e33","resolution":{"observed_at":"2026-08-10T23:16:12.031544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:12.012799Z","title":"Wasserstein gan, 2017","venue":null,"work_id":"8d08da88-247f-4a93-b778-4e86bab2af44","year":2017},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.029005Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:f3ef419b30ef613fad22e818d853e1016917c90872bcdc54504ceb0a4721c175","observation_id":"9fbe6cf2-8509-4691-b171-b22c16691152","resolution":{"observed_at":"2026-08-10T23:16:12.017276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.997304Z","title":"Text2gestures: A transformer-based network for generating emotive body gestures for virtual agents","venue":null,"work_id":"4dfae308-ae32-4563-a974-22ac3aedf0e8","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.034102Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:7ce13c031eda3e22b4ba259c9a98d8825bd640e3c29be80629e4d947857edb64","observation_id":"84e421b2-575b-4c10-a1b3-1cfe9e0c4aa5","resolution":{"observed_at":"2026-08-10T23:16:12.002073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.982115Z","title":"Implicit neural representations for variable length human motion generation","venue":null,"work_id":"f98fb436-3a77-4e1e-aabe-799b5b3014ea","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.038992Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c16528e6829c90bcfea96b005a160197d4cb4e013b67709020644e892d4f5fd8","observation_id":"78837075-95f0-416b-9702-48c52756bc5c","resolution":{"observed_at":"2026-08-10T23:16:11.987191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.966194Z","title":"Executing your commands via motion diffusion in latent space, 2023","venue":null,"work_id":"e8c14e2c-3bc0-4655-99b1-e514b392fec5","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.043969Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:25ae9aea196592782d084da25c80f78351fa78b35b87d368c2a209f86502518c","observation_id":"ec87e671-b44f-4e08-9cf0-f8d66826a16a","resolution":{"observed_at":"2026-08-10T23:16:11.971704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.951455Z","title":null,"venue":null,"work_id":"365b49b7-2024-480a-a536-55f3faeae493","year":2000},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.048384Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:2ad6c619dcfaf0832adcc081660bafd03ad2924cb4a546a68b3eb6f53bd38ad5","observation_id":"c526bbfd-3f64-44e3-a27f-21121e3f285f","resolution":{"observed_at":"2026-08-10T23:16:11.955941Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.936316Z","title":"Synthesis of compositional animations from textual descriptions","venue":null,"work_id":"0ea4b165-646f-427c-b2db-61ebf394e36b","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.052904Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:7a840090359534eece5439b39b43d1f0b0976f82fb488a7dbeddad01fb37331f","observation_id":"34567a25-44e8-4ffb-8f7b-26230260a63b","resolution":{"observed_at":"2026-08-10T23:16:11.941037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.057288Z","title":"Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.057288Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:1f9357eed7316749e064a4ade0b2320057d82a7ab37c486e6129361fd2926dee","observation_id":"d51f55db-253d-43c3-812f-8015428c29b6","resolution":{"observed_at":"2026-08-10T23:16:11.057288Z","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":"2026-08-10T23:16:11.910466Z","title":"Improved training of wasserstein gans, 2017","venue":null,"work_id":"86c3ce9b-bed4-4b7b-aa8b-7ec3cc3de16a","year":2017},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.061983Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:4735b300da71ada50adf1ddf9c850a4001502f697491299dce9fc774438ee6c0","observation_id":"933daf29-7e5a-4788-bcdc-47017462d9ec","resolution":{"observed_at":"2026-08-10T23:16:11.915850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.01696","last_updated":"2022-08-04T18:31:20Z","snapshot_observed_at":"2026-08-13T15:10:42.366306Z","submitted_at":"2022-07-04T19:52:18Z","title":"TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.01696","snapshot_observed_at":"2026-08-10T23:16:11.066204Z","title":"Tm2t: Stochastic and tokenized modeling for the reciprocal genera- tion of 3d human motions and texts","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.066204Z"},"links":{"cited_paper":"/paper/2207.01696","citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:1a4bd7f3258feaf12a3e41397bd2d9a5168ef29a4ab5904560b71aaa6a4979fb","observation_id":"cb024db1-24e9-469d-9bc5-a832c373eb47","resolution":{"observed_at":"2026-08-10T23:16:11.066204Z","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":"2026-08-10T23:16:11.896330Z","title":"Generating diverse and natural 3d human motions from text","venue":null,"work_id":"1d4bf389-eb8d-4cc9-9fec-a4a56cbebe38","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.071155Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:b0aacc31e2b580340098e6f540872d686ad6a6d4cfc92045ace807769f49e264","observation_id":"e63082f1-e659-4f50-94c5-cd8f2b93e4b6","resolution":{"observed_at":"2026-08-10T23:16:11.901114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.882332Z","title":"Generating diverse and natural 3d human motions from text","venue":null,"work_id":"77b2f0c4-9145-4c6b-904b-ab0ca222e601","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.075604Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:fa321698e9ff5ad626de8c14ddb04618b52bf9b0f754153a372f1bdece6ab336","observation_id":"c970a29c-b6fb-42f6-a934-6c7b840caec4","resolution":{"observed_at":"2026-08-10T23:16:11.886898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.867530Z","title":"Generating diverse and natural 3d human motions from text","venue":null,"work_id":"a281a756-c91c-4d7e-aa2b-48d6a01770a6","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.079843Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:56250d46797f9f79cc5e0e808c52f21a22c51bd99e0c93313c136c68411671a3","observation_id":"792d8f80-a761-47e6-b647-9915b3d1c009","resolution":{"observed_at":"2026-08-10T23:16:11.872375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.852961Z","title":"Ac- tion2motion: Conditioned generation of 3d human motions","venue":null,"work_id":"253682a5-607e-4dc0-a3c1-e345bb9c95ac","year":2020},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.084104Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:b2336470f7634f8436611b96086872a6e93901f2e59548c75ca30e3b5283fa5b","observation_id":"224c31f3-80a2-44a2-8b03-6e6196d9de46","resolution":{"observed_at":"2026-08-10T23:16:11.857666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.088587Z","title":"Deep residual learning for image recognition, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.088587Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c85ef75275e7cbade823fceae053af9668f63aa9bc67266f141720b6f2cca36b","observation_id":"df8c1a2e-234e-4972-892a-83df38bc035d","resolution":{"observed_at":"2026-08-10T23:16:11.088587Z","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":"2026-08-10T23:16:11.092964Z","title":"Denoising diffu- sion probabilistic models, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.092964Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:9f847140f0ee09ba23183f25d858cc653b962901c4578c89bd8c5be741347a98","observation_id":"b9b16d98-5f18-4819-96aa-961ca8ae9bd5","resolution":{"observed_at":"2026-08-10T23:16:11.092964Z","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":"2026-08-10T23:16:11.819886Z","title":"Motiongpt: Human motion as a foreign language,","venue":null,"work_id":"cb24be10-6fe9-4ac3-be7c-ea26fe3862a6","year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.097689Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:d68a093f8246e4f4f7f71166a10b418a04a1dcf02ed45126e1b9048c88a47af8","observation_id":"91002c56-a7ae-407a-a34a-c769f2d40807","resolution":{"observed_at":"2026-08-10T23:16:11.824154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.805504Z","title":"Scaling up gans for text-to-image synthesis, 2023","venue":null,"work_id":"4b332d9d-e20a-4ac2-985b-66afba1686ab","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.102442Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:8e341dd2cb54f5ae0ba0bf27d51e93543ff89e877613b68a9572c2f69b71e429","observation_id":"03442d09-cdf6-4491-b715-65766529e6b9","resolution":{"observed_at":"2026-08-10T23:16:11.810325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.791905Z","title":"Audio-driven facial animation by joint end- to-end learning of pose and emotion","venue":null,"work_id":"bcdba857-1485-40cb-892a-c635f1f1cbd2","year":2017},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.107104Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:8e91f13c66de5a2ebb631d67de1df6dbd6d55e41af8389d5de6456b6706430d6","observation_id":"6569aea6-76f1-4731-95a9-aa0d79399e79","resolution":{"observed_at":"2026-08-10T23:16:11.796323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.111543Z","title":"A style-based generator architecture for generative adversarial networks,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.111543Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:664431693021f0ee9763864744e2b38fbe3f063e94bd4a68300cf60c3c04d70a","observation_id":"ae1057f5-e1f7-453f-91ab-22b8522a3d02","resolution":{"observed_at":"2026-08-10T23:16:11.111543Z","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":"2026-08-10T23:16:11.768004Z","title":"Flame: Free- form language-based motion synthesis & editing","venue":null,"work_id":"da0a849e-2700-4ef5-a492-7204fad7bae6","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.116169Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c62fefccda66120b021f4229ac80c59fe4b0acc7187d92b858baa985d84fe1b5","observation_id":"47bd66a8-9da9-4822-91b6-220d864223d1","resolution":{"observed_at":"2026-08-10T23:16:11.772647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.752740Z","title":"Flame: Free- form language-based motion synthesis & editing, 2023","venue":null,"work_id":"182eecf8-fe55-4087-b3eb-a3011bc787a6","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.120303Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:2101b03f162bb1f7e0c4431b68c4337ff87773dac6d0ceb13f34ec579a458543","observation_id":"38239968-1167-4434-bc7b-386b61aa87d0","resolution":{"observed_at":"2026-08-10T23:16:11.758158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.738126Z","title":"Dance- former: Music conditioned 3d dance generation with para- metric motion transformer","venue":null,"work_id":"fe409c67-bf4b-482e-8949-44c5714dffcc","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.124731Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:0576f2684aebcae28ad77db07277b4233718823164b66586842f8ae35e4c35b7","observation_id":"174a2ce8-b7db-430a-a7f6-9c59fa0ed72d","resolution":{"observed_at":"2026-08-10T23:16:11.743170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.723947Z","title":"Ganimator: neural motion synthesis from a single sequence","venue":null,"work_id":"73eba4c6-ea87-470d-a921-cf90f13985a1","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.129487Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c8b412cc9345d545485ca18b9834a86d5fbf08c6961d5f8fbd5fa37a58672341","observation_id":"a4a39087-b791-4d73-be48-dd443a42474d","resolution":{"observed_at":"2026-08-10T23:16:11.728636Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.709732Z","title":"Ross, and Angjoo Kanazawa","venue":null,"work_id":"4c583f49-585f-4022-85e2-29f902815bea","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.133912Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:406d8d2bf0e9142e4ed13da027949bed019b85f92362ce9c1377b68ebc34d759","observation_id":"00aa1534-418d-47f5-b27b-da40670b21ee","resolution":{"observed_at":"2026-08-10T23:16:11.714308Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.695087Z","title":"Ross, and Angjoo Kanazawa","venue":null,"work_id":"5f4ae0b4-028d-48eb-b2d5-1584088df018","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.138053Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:89556a0da1a37f2db41016bb7c95ddeb619454b1532a44e6d9d836ae09292c6b","observation_id":"441661c2-4563-42dd-88f0-8eaf52579a67","resolution":{"observed_at":"2026-08-10T23:16:11.699809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.680650Z","title":"Piano: A parametric hand bone model from magnetic reso- nance imaging","venue":null,"work_id":"b724e638-706f-4c21-b2d8-343fa6704df7","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.142218Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:091b7be7f1d711ce4441690f9ef593f53428d3479a60e22e93d139603913fbac","observation_id":"e2cee6eb-c34d-4685-b056-6c8f905319cd","resolution":{"observed_at":"2026-08-10T23:16:11.685192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.665673Z","title":"A comprehensive survey on knowledge distil- lation of diffusion models, 2023","venue":null,"work_id":"83d2622b-ad21-4ff7-a9bd-d4b005f16863","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.146129Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:27d301737a559e1ee205d4e5f79f3611cd1453d0d68e5f339db8a19cdfe660ae","observation_id":"2663c723-235f-48fc-bf7d-bab013876ca1","resolution":{"observed_at":"2026-08-10T23:16:11.670923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.650299Z","title":"Troje, Ger- ard Pons-Moll, and Michael J","venue":null,"work_id":"3cd777d5-e481-4186-8ed0-073fb210913f","year":2019},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.150411Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c5bb8170a1c33eb8ddaf8ee52075cd80c39357c9dc7fad60971f0e6286873c50","observation_id":"5af40e99-5c23-4948-bb7f-b085ca5ef62f","resolution":{"observed_at":"2026-08-10T23:16:11.655106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.635899Z","title":"Conditional generative adversarial nets, 2014","venue":null,"work_id":"ace9afb7-a379-4b2c-b320-20589fbc2fb6","year":2014},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.154644Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:48269f694d3cb9ccf1af63db11dd3de3f1734ae034d05e44c7df977ae1b79c21","observation_id":"b6ee7aac-af6b-40c9-bdad-426f63fe7688","resolution":{"observed_at":"2026-08-10T23:16:11.640387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.620931Z","title":"Black, and G ¨ul Varol","venue":null,"work_id":"e8affe3a-708b-4d15-a73e-a73855489cfa","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.158579Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:aa8ce827763af9dbb4e93d3f2a6c39f76080c67d0dab759143d237fb9f79df7d","observation_id":"49173bec-270b-42e8-beb3-dd4ff655c29a","resolution":{"observed_at":"2026-08-10T23:16:11.625356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.14109","last_updated":"2022-07-22T09:07:31Z","snapshot_observed_at":"2026-08-13T15:55:54.844432Z","submitted_at":"2022-04-25T14:53:06Z","title":"TEMOS: Generating diverse human motions from textual descriptions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.14109","snapshot_observed_at":"2026-08-10T23:16:11.162950Z","title":"Black, and G ¨ul Varol","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.162950Z"},"links":{"cited_paper":"/paper/2204.14109","citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c7b2f3a54a3079bcac4e8e4134d9d3fdde68a51b8000bd8f2bc638b7d61243d0","observation_id":"052481f5-17f9-4ee9-8582-121e999a63a9","resolution":{"observed_at":"2026-08-10T23:16:11.162950Z","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":"2026-08-10T23:16:11.606884Z","title":"Black, and G ¨ul Varol","venue":null,"work_id":"35321584-a549-4c01-843f-6381bcd5b514","year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.168180Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:a906a2e6935a3a3f38cd88d60d2f65743127c746f7503a60d1991e4f43e5ef63","observation_id":"0f5bfeec-8a41-40b1-bdd2-dc383226b14f","resolution":{"observed_at":"2026-08-10T23:16:11.611092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.593296Z","title":"Black, and G ¨ul Varol","venue":null,"work_id":"c24f0e17-e39f-4377-bf96-ce7fc035be0e","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.172896Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:c931b577c09f4fc1f3443232791ce7a3f344f65c9b46f614f8ecaae82d435c3e","observation_id":"0f57e5c2-ba43-4366-8b55-1c87d14526e0","resolution":{"observed_at":"2026-08-10T23:16:11.597326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.578995Z","title":"Learning a bidirectional mapping between human whole- body motion and natural language using deep recurrent neu- ral networks","venue":null,"work_id":"79d22f77-32f9-4209-9443-34030abedff3","year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.177566Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:f450c9adbea2cffe48a5d0cdb6072b17ee7bb10b47751f5387112e6cc56a4758","observation_id":"92d26bff-55a8-42d2-8f37-536f30cb20a1","resolution":{"observed_at":"2026-08-10T23:16:11.583648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.564192Z","title":"Modi: Un- conditional motion synthesis from diverse data, 2022","venue":null,"work_id":"6249385a-9ab3-473a-9c82-a2c8a150e42c","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.182410Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:26546b962cd06fd826536469f020b6c3ea54ed5c34f28aee8ba125690af32c3c","observation_id":"bef25f10-b804-416b-9d6f-b1111c494c9d","resolution":{"observed_at":"2026-08-10T23:16:11.569057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.187051Z","title":"Learning transferable visual models from natural language supervision, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.187051Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:f7664607731f4424e618a36e3432ccf7dcbd5d002bdea2dfb8484d036c9e40e0","observation_id":"3cb0f187-7733-4635-b379-4ea4605ff875","resolution":{"observed_at":"2026-08-10T23:16:11.187051Z","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":"2026-08-10T23:16:11.191545Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.191545Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:7f1a2b15bcb6fea37737c2b2f51299be27f6692c9f7b09534f88a73f9437e1ce","observation_id":"31d818bd-df93-4887-b5ba-59c958a3405b","resolution":{"observed_at":"2026-08-10T23:16:11.191545Z","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":"2026-08-10T23:16:11.195791Z","title":"High-resolution image syn- thesis with latent diffusion models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.195791Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:89d5d5d95f48bdd0383dd7756c27d2f7aee078fc5a78064372f65128413e6529","observation_id":"0afc92fc-dd37-4b82-8361-3408229ca29a","resolution":{"observed_at":"2026-08-10T23:16:11.195791Z","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":"2026-08-10T23:16:11.200286Z","title":"Improved techniques for training gans, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.200286Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:ec9de30193534943d370755bf8d36f9b314b23dc7dcab8021b7f6130f14d7080","observation_id":"8abadc15-eb66-4b31-89cd-57ceb94f6843","resolution":{"observed_at":"2026-08-10T23:16:11.200286Z","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":"2026-08-10T23:16:11.509528Z","title":"Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis, 2023","venue":null,"work_id":"7c6e86c7-c432-4eab-a09f-699ade4598bd","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.204952Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:e6c4294df9ae3e65d5ecedb492e27db7591a2a86b8f46cedd1230871afddda68","observation_id":"de340bcb-d8a5-48f1-b20e-198d433b8393","resolution":{"observed_at":"2026-08-10T23:16:11.515210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.493262Z","title":"Adversarial diffusion distillation, 2023","venue":null,"work_id":"7e0b3627-8872-45cb-bfaa-0529ecebafe5","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.209440Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:748132e8e6dedf11c44dda9aa617109de7c0771fdf2b52e488b50c5e5097e1df","observation_id":"0ad9816d-b9e3-4dbb-9ede-3f1774633ee6","resolution":{"observed_at":"2026-08-10T23:16:11.498322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.477599Z","title":"Generative adversarial net- works (gans survey): Challenges, solutions, and future direc- tions, 2023","venue":null,"work_id":"1772a8db-a83d-4c20-afc7-8de7405a0a92","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.213653Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:764e10928472618d5819440bab57e07fddb660f1d28ca34219b86196fd8e9553","observation_id":"ad483e81-8a96-4e68-8c05-42a98ee20f6d","resolution":{"observed_at":"2026-08-10T23:16:11.482816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.461901Z","title":"Human motion gen- eration using wasserstein gan","venue":null,"work_id":"db334eca-66bc-4760-88f8-b2f5b4118e5d","year":2021},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.218151Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:b1d4b18465fa9713022c12241f779bf5da0e3f0d36ac8b0e8c445e673fa37e83","observation_id":"7eb3732b-f45f-4c4d-ae4c-d1efbb73d5d2","resolution":{"observed_at":"2026-08-10T23:16:11.467092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.446898Z","title":"Bermano, and Daniel Cohen-Or","venue":null,"work_id":"8827de77-37b1-4987-82a0-fb81e05ee321","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.222632Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:947e0bd67be21921b4071792de354f2c5ee3dc5cc95354c18323f87bc27caf3a","observation_id":"b4aef9e7-6fbf-4c75-a543-c8f83acd1d5a","resolution":{"observed_at":"2026-08-10T23:16:11.451490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14916","last_updated":"2022-10-03T09:17:41Z","snapshot_observed_at":"2026-08-12T18:48:37.916493Z","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":"2026-08-10T23:16:11.231537Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.231537Z"},"links":{"cited_paper":"/paper/2209.14916","citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:1df72c4975cd379943d1a3e9c567164a487f59c05a777ff698dfababe505ccca","observation_id":"1709d659-ef1c-4fa6-8dbd-f0ce73918b93","resolution":{"observed_at":"2026-08-10T23:16:11.231537Z","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":"2026-08-10T23:16:11.431576Z","title":null,"venue":null,"work_id":"5b2d8477-de20-49ea-8c2e-c0c59996acff","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.236215Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:68174d95070b37ae831ea13c87c085dc0d937fd661779c5fe9cbd7a4ceadca53","observation_id":"4467f1f9-10ff-4f32-adb8-f8b053f54508","resolution":{"observed_at":"2026-08-10T23:16:11.436299Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.241729Z","title":"Neural discrete representation learning,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.241729Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:3f8e3ac5b44a088f313c98d7b940a35086204fa8802522832ea49e3a96b967b9","observation_id":"cf6cccab-36fc-4e0a-94cb-473f31139086","resolution":{"observed_at":"2026-08-10T23:16:11.241729Z","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":"2026-08-10T23:16:11.407653Z","title":"Actformer: A gan- based transformer towards general action-conditioned 3d hu- man motion generation, 2022","venue":null,"work_id":"8d72da04-1338-46b4-85c4-231298ccd991","year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.246942Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:4ac2f93f53e7d2dd763ecace6e7cc76543adf05cbfc401e5d9e48b41aeb94d14","observation_id":"90140290-0bc8-4dc7-b2f7-8ab647248681","resolution":{"observed_at":"2026-08-10T23:16:11.412255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T23:16:11.251719Z","title":"Freeman, and Taesung Park","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.251719Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:ece2e1afb35c02984cab9776a674d67f51076ac56e03591cf853f782784edeaf","observation_id":"d1157c31-39a5-4316-b761-ccc8d85d8a10","resolution":{"observed_at":"2026-08-10T23:16:11.251719Z","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":"2026-08-10T23:16:11.380841Z","title":"T2m-gpt: Generating human motion from textual de- scriptions with discrete representations, 2023","venue":null,"work_id":"ef92f07f-2e42-4037-8e9b-88a580f71c69","year":2023},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.255872Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:a5747d11bdd8aa6d84e4db8cd0286f07cabb3de1b3b01eed3a9a920190fde547","observation_id":"f3e462c8-859b-4711-82d8-e46270f0033d","resolution":{"observed_at":"2026-08-10T23:16:11.386463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.15001","last_updated":"2022-08-31T17:58:54Z","snapshot_observed_at":"2026-08-13T14:35:06.773752Z","submitted_at":"2022-08-31T17:58:54Z","title":"MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.15001","snapshot_observed_at":"2026-08-10T23:16:11.260131Z","title":"Motiondif- fuse: Text-driven human motion generation with diffusion model","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.260131Z"},"links":{"cited_paper":"/paper/2208.15001","citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:336581efec8bbd389fd29f1fe420f93db4f32976e076d039b4abc85322256db6","observation_id":"25b0f392-3cc4-4249-990c-469620395154","resolution":{"observed_at":"2026-08-10T23:16:11.260131Z","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":"2026-08-10T23:16:11.363084Z","title":"LS-GAN qualitative results on text-to-motion: a.A person is skipping rope","venue":null,"work_id":"b079a1ed-3510-46d4-9b61-ad0e0264cd26","year":null},"citing_paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T23:16:11.265253Z"},"links":{"citing_paper":"/paper/2501.01449"},"observation_digest":"sha256:6a84c09ba9819b931d0f89f84ac6332d24b8c33eb53bc292ba4da636155373de","observation_id":"5f8b2f02-e82d-46a4-98db-cda688d766b4","resolution":{"observed_at":"2026-08-10T23:16:11.369671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.01449","last_updated":"2024-12-30T05:44:38Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T20:50:01.654928Z","submitted_at":"2024-12-30T05:44:38Z","title":"LS-GAN: Human Motion Synthesis with Latent-space GANs"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":0,"verified_fuzzy":39},"total_outbound_references":55},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2501.01449."}