{"as_of":"2026-08-17T15:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:df96585a1598ccd5c8780464a62ce296f434ca70adbc590b09d916ecb9079e94","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T22:21:22.443646Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2505.07901/citation-record","integrity":"/paper/2505.07901/integrity","json":"/paper/2505.07901/citation-record.json","paper":"/paper/2505.07901"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:21:23.209838Z","title":"the MIT Press, 1974","venue":null,"work_id":"9f4b8e89-40df-4820-a53e-8d4ab915b7fd","year":1974},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.217064Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:2892f6eca0e28c6d2436e7e15e8b38248d57b4a45094e3213abbb59b716944d3","observation_id":"9d83d035-47a1-4945-8f43-0492fbe38ad1","resolution":{"observed_at":"2026-08-15T22:21:23.215550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.193304Z","title":"The sor (stimulus-organism- response) paradigm in online learning: an empirical study of students’ knowledge hiding perceptions","venue":null,"work_id":"909806fe-d1c8-4385-848d-1c6dae2bfcf3","year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.222974Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:b2b14178abf2757caaaee325fb57f8117772652b69d7f49ad7e0e9f57a89e154","observation_id":"e73fb36b-80bd-42cc-8b3d-9ddf9e31ead2","resolution":{"observed_at":"2026-08-15T22:21:23.198283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.177510Z","title":"The affec- tive facial recognition task: The influence of cognitive styles and exposure times","venue":null,"work_id":"a2fd1051-8b4e-48f2-8a88-ac0c937db1be","year":2019},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.228575Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:dcf72f3c7191fa84610d1fd5b9b5948fd7c407459d7ffcd13bc7d381e635997b","observation_id":"83629d59-6ff0-43a6-b74e-c136f5ec9c49","resolution":{"observed_at":"2026-08-15T22:21:23.182440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.160828Z","title":"Comparison of spatio-temporal models for human motion and pose forecasting in face-to-face interaction scenarios supplementary material","venue":null,"work_id":"d242f6c4-bccc-4c1c-8458-330fa33c595e","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.233551Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:64cfc45a8bb81d41aa88920b9c2ec50d02a9e19c848d64ed9e280ae9c45113c4","observation_id":"6ef10c48-37d4-438f-b9e7-f3c9f37d7174","resolution":{"observed_at":"2026-08-15T22:21:23.165972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.141529Z","title":"Dyadgan: Generating facial expressions in dyadic interactions","venue":null,"work_id":"dc16ca56-721b-445c-b6c2-34a0af59642a","year":2017},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.238917Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:8cb37a81212d01535834c575e00c0a066997374b4db108a8fcbe12bb91209e30","observation_id":"041f5c1c-346e-45a6-a614-77bb91387949","resolution":{"observed_at":"2026-08-15T22:21:23.148818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.123347Z","title":"Chalearn lap challenges on self-reported personality recognition and non-verbal behavior forecasting during social dyadic interactions: Dataset, design, and results","venue":null,"work_id":"9ec5d311-43b8-4599-a25a-e0cf9268afd2","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.244248Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:490a4272277cce8de148750ce2cdc86dc42a47f2a6c0b52e38a2d34deb115693","observation_id":"da8caa73-c73f-4829-a1dc-012333c84038","resolution":{"observed_at":"2026-08-15T22:21:23.128641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.105698Z","title":"Personality recognition by modelling person-specific cognitive pro- cesses using graph representation","venue":null,"work_id":"9b07e686-990b-49fe-8928-e64bf1c2e651","year":2021},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.250298Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:74ede5206f35a75eceb6ed88800b0e879c5ecd260ec89da66c1bcff01f0b02bd","observation_id":"0ee5d0c6-8b1d-42b9-8c60-86b94ef34068","resolution":{"observed_at":"2026-08-15T22:21:23.111828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.087087Z","title":"Learning person-specific cognition from facial reactions for automatic personality recognition.IEEE Transactions on Affective Computing, 14(4):3048– 3065, 2022","venue":null,"work_id":"970ea379-6daa-4c76-9453-6bada0f64f4e","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.255750Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:e34cbca6aa9cdf5435dd39e3ce88cb06be55385fa037e076098f8efa57124ea4","observation_id":"01bb0ef8-2a81-4170-90cc-bf5153e0f92c","resolution":{"observed_at":"2026-08-15T22:21:23.092829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.069511Z","title":"Re- sponsive listening head generation: a benchmark dataset and baseline","venue":null,"work_id":"430f84c7-14f0-46b3-8ed6-6e0e10cfd7c8","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.260518Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:d0f0de9dd70d97516ba90c9fc9ead7a499d6cdd052df05d67585e54f224d717f","observation_id":"30b7b5a8-37b1-41ae-b88c-02da27e1b0c7","resolution":{"observed_at":"2026-08-15T22:21:23.075076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.051900Z","title":"Learning to listen: Modeling non-deterministic dyadic facial motion","venue":null,"work_id":"03425cad-a443-40f4-8cd2-96b03422d2db","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.265543Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:a02e2e20af0c99ac3059bc23d220c32f387796a0cb8435001f0bef03eea77085","observation_id":"7b80c69a-14f5-4128-8f78-9e75e942b56a","resolution":{"observed_at":"2026-08-15T22:21:23.057559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06514","last_updated":"2023-03-23T16:58:41Z","snapshot_observed_at":"2026-08-16T15:55:41.059028Z","submitted_at":"2023-02-13T16:49:27Z","title":"Multiple Appropriate Facial Reaction Generation in Dyadic Interaction Settings: What, Why and How?","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06514","snapshot_observed_at":"2026-08-15T22:21:22.270729Z","title":"Multiple appropriate facial reaction generation in dyadic interaction settings: What, why and how?arXiv preprint arXiv:2302.06514, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.270729Z"},"links":{"cited_paper":"/paper/2302.06514","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:bc4108e65cf3321451bbe4d649e2c936c3fbde9369c6e7ac1d4e99a726c0db8d","observation_id":"b9781c47-783d-40aa-9323-6f5622821d1d","resolution":{"observed_at":"2026-08-15T22:21:22.270729Z","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":"2026-08-15T22:21:22.276739Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.276739Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:f7c3941fdf1af11161898f01bfe68606d067ea887cc305c15f4ff7789dfa45a5","observation_id":"2f97b6b6-befb-4e59-b400-4a0b7ce99255","resolution":{"observed_at":"2026-08-15T22:21:22.276739Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.05166","last_updated":"2024-01-10T14:01:51Z","snapshot_observed_at":"2026-08-16T14:28:31.643518Z","submitted_at":"2024-01-10T14:01:51Z","title":"REACT 2024: the Second Multiple Appropriate Facial Reaction Generation Challenge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.05166","snapshot_observed_at":"2026-08-15T22:21:22.282105Z","title":"React 2024: the second multiple appropriate facial reaction generation challenge","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.282105Z"},"links":{"cited_paper":"/paper/2401.05166","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:7a28ac6e2b4f975407ea82f752eae266980319a5b656e49a2130781303c31c36","observation_id":"c371371c-47a9-4401-aae0-57891c670d0a","resolution":{"observed_at":"2026-08-15T22:21:22.282105Z","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":"2026-08-15T22:21:23.022628Z","title":"Responsive listening behavior.Computer animation and virtual worlds, 19(5):579–589, 2008","venue":null,"work_id":"ee4a724f-ebe6-4123-a13e-7a8f6e2f71df","year":2008},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.287732Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:5b263bf243df0e0c35c980c82f347a89e6f55368a38c0028ad7a46e0a703e1a7","observation_id":"931e5f74-c54b-478c-b274-fae07994dcb7","resolution":{"observed_at":"2026-08-15T22:21:23.027973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:23.003392Z","title":"To react or not to react: End-to-end visual pose forecasting for personalized avatar during dyadic conversations","venue":null,"work_id":"eef5a4ca-b839-4a20-b1ae-e5c1bea9327f","year":2019},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.292691Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:9f5436b5cac9267a7238e2e29c9d51ab3dd38e74e5526c347133adb31299998a","observation_id":"bad65db0-334e-4a9e-b014-214d20e9277a","resolution":{"observed_at":"2026-08-15T22:21:23.010293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.986298Z","title":"Predicting head pose in dyadic conversation","venue":null,"work_id":"78ec1483-ef71-4f7e-8065-50ab0d109c5b","year":2017},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.297563Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:5cc62be18e82c35a71632a884cf7d3b53d4444772a5cedda6bef380730761a5f","observation_id":"54b3196f-d6d5-4f7e-bfcf-d8f630212a20","resolution":{"observed_at":"2026-08-15T22:21:22.991324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10939","last_updated":"2023-01-26T05:00:09Z","snapshot_observed_at":"2026-08-16T16:00:04.764118Z","submitted_at":"2023-01-26T05:00:09Z","title":"Affective Faces for Goal-Driven Dyadic Communication","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10939","snapshot_observed_at":"2026-08-15T22:21:22.302504Z","title":"Affective faces for goal-driven dyadic communication.arXiv preprint arXiv:2301.10939, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.302504Z"},"links":{"cited_paper":"/paper/2301.10939","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:101e2e08f1cb732229bd237598bbf49c038fa3055fe0bb898b2a14e70b010e40","observation_id":"7bbf77f5-ac33-4dcd-9648-8af9d687f777","resolution":{"observed_at":"2026-08-15T22:21:22.302504Z","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":"2026-08-15T22:21:22.308046Z","title":"Generative adversarial net- works.Communications of the ACM, 63(11):139–144, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.308046Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:f05715a2292e00217aa6b56e1bfde658c6a7dab2d8f1ea925c125f286beee3cb","observation_id":"affbe450-dde9-4401-a13d-2ff18319be9b","resolution":{"observed_at":"2026-08-15T22:21:22.308046Z","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":"2026-08-15T22:21:22.957419Z","title":"Context-aware human behaviour forecasting in dyadic interactions","venue":null,"work_id":"807d247e-dc58-4de9-8cea-c5107f0d3020","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.313932Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:a6a28540419acd9bbe85c2f9e3b720d2eb3ac0d0cb96cc3205cc7510487ddb95","observation_id":"22317c20-cb43-4960-a903-5db0b1f0b8b1","resolution":{"observed_at":"2026-08-15T22:21:22.962698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.320290Z","title":"Long short-term memory.Supervised sequence labelling with recurrent neural networks, pages 37–45, 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.320290Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:cfd92cf295ae95b3b4110a77924e7e7f4c4969112b1d57c4452a2da953b84417","observation_id":"47c90ba2-f437-4285-8162-15ce4b73b658","resolution":{"observed_at":"2026-08-15T22:21:22.320290Z","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":"2026-08-15T22:21:22.928459Z","title":"A morphable model for the synthesis of 3d faces","venue":null,"work_id":"2ead6997-a13d-4363-89c8-8c756f2dce49","year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.325766Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:1d418dcacbdac0a32b21a41172c23b00ac3caeccbb00e4595cf6555f2fe36bb9","observation_id":"90ab26e6-b7a5-4b25-be1f-b98c15829d60","resolution":{"observed_at":"2026-08-15T22:21:22.933870Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.331608Z","title":"Neural discrete representation learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.331608Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:db90205f5f6014c7c7612603a1c3f33d1c3d0542d66d81d6a4c83a9bc37c73bf","observation_id":"7e268714-aa20-4f45-9b9c-4ab5dd819b02","resolution":{"observed_at":"2026-08-15T22:21:22.331608Z","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":"2026-08-15T22:21:22.898705Z","title":"Emo- tional listener portrait: Neural listener head generation with emotion","venue":null,"work_id":"aeb5cb73-4402-4fa4-a173-4e75af0204a3","year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.336660Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:6a5a6a7d975db875b3109def2cbd69feaca1e67301f75ccdc3231a1a0d007476","observation_id":"20c947b2-634c-4006-ac4d-461a7391c791","resolution":{"observed_at":"2026-08-15T22:21:22.904093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.06583","last_updated":"2023-06-11T04:15:56Z","snapshot_observed_at":"2026-08-16T15:24:51.646518Z","submitted_at":"2023-06-11T04:15:56Z","title":"REACT2023: the first Multi-modal Multiple Appropriate Facial Reaction Generation Challenge","version":1},"cited_work":{"arxiv_id":"2306.06583","doi":null,"metadata_source":"pith","pith_arxiv_id":"2306.06583","snapshot_observed_at":"2026-08-15T22:21:22.564155Z","title":"REACT2023: the first Multi-modal Multiple Appropriate Facial Reaction Generation Challenge","venue":"cs.CV","work_id":"a823dd9e-44a3-4d53-b491-2c53810c6cc5","year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.341878Z"},"links":{"cited_paper":"/paper/2306.06583","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:95fff37194e84505b69c9a60b575c5fd187c4cf58f5e31035f22fea7d7fd6433","observation_id":"7e651156-0d17-4d41-b563-8fb5588e823f","resolution":{"observed_at":"2026-08-15T22:21:22.572254Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.878577Z","title":"Finite scalar quantization as facial tokenizer for dyadic reaction generation","venue":null,"work_id":"a9c0e5a7-6bd2-4eac-82a2-3d3a75c75fff","year":null},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.346880Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:addfd172b059ba8466e7b61a7935acc638b5e05d3cac00cd112933eefadcb868","observation_id":"3bd2b105-9b0a-41ca-96a6-db108bbbee00","resolution":{"observed_at":"2026-08-15T22:21:22.884166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.861556Z","title":"One-to-many appropriate reaction mapping mod- eling with discrete latent variable","venue":null,"work_id":"dc78adb0-b962-459f-9932-59e132571323","year":null},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.351694Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:5245885770e1dd8fc79022be16f9873003a42f98248af3bfaf1bc6af2687a6ae","observation_id":"62030e86-8ad4-4a43-b0de-a32b19857c2b","resolution":{"observed_at":"2026-08-15T22:21:22.867058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.842634Z","title":"Multiple facial reaction generation using gaussian mixture of models and multimodal bottleneck transformer","venue":null,"work_id":"69f48322-c69f-4d09-b1b5-0d19023ffec8","year":2024},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.356494Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:fe38daddd78c2a9b1934a6dfda7bf4ec07c6065bc8cb62e2e8ae76a7a534e1cf","observation_id":"04f87831-50ad-4ea7-bd86-19c0c862c404","resolution":{"observed_at":"2026-08-15T22:21:22.848268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.822652Z","title":"Vector quantized diffusion models for multiple ap- propriate reactions generation","venue":null,"work_id":"83ebd1a5-bc54-4fef-9e1b-5f0ace70595c","year":2024},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.361409Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:4856d4bdedf02315c03bc2980131fc5ea1f4013c15e3e4ec84fed54728ef4b8e","observation_id":"7cd2f16e-d2b1-474a-bc60-1cf216292b65","resolution":{"observed_at":"2026-08-15T22:21:22.829443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.804839Z","title":"Diffusion autoencoders: Toward a meaningful and decodable rep- resentation","venue":null,"work_id":"581e6481-fbc7-412c-9027-847ecd312fe2","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.367391Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:11af302648b77a4a645e76cc9c5a5c72a1d9ca21d630ed1fbd4fe21a63393da0","observation_id":"e9a9d17a-a8f1-4d1c-8812-4c933058787d","resolution":{"observed_at":"2026-08-15T22:21:22.810716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.09778","last_updated":"2022-10-31T09:05:25Z","snapshot_observed_at":"2026-08-16T17:20:02.890207Z","submitted_at":"2022-02-20T10:37:52Z","title":"Pseudo Numerical Methods for Diffusion Models on Manifolds","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.09778","snapshot_observed_at":"2026-08-15T22:21:22.372823Z","title":"Pseudo numerical methods for diffusion models on manifolds.arXiv preprint arXiv:2202.09778, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.372823Z"},"links":{"cited_paper":"/paper/2202.09778","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:e43fb49f3e7d8fb16e8ce4289e2fd687097165056e7bc35e9a6b6538c96b7b17","observation_id":"e4ab73f9-d92a-49ef-8e44-9eae473f28ce","resolution":{"observed_at":"2026-08-15T22:21:22.372823Z","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":"2026-08-15T22:21:22.379061Z","title":"Denoising diffusion probabilistic mod- els.Advances in neural information processing systems, 33:6840–6851, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.379061Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:30f4777a76776a78a9b54bedb6ed65da0610a05e0ff820aef2bacca26663faf3","observation_id":"b5a73a16-e238-437c-923c-bdd027d896bd","resolution":{"observed_at":"2026-08-15T22:21:22.379061Z","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":"2026-08-15T22:21:22.774105Z","title":"The noxi database: multimodal recordings of mediated novice-expert interactions","venue":null,"work_id":"bf0694bd-701f-417a-a668-447986f2801b","year":2017},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.384243Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:3089c2a1a8e6149f560d32f8be8aa6a4bd432a2974db81fc57f7b0dc7b8e2439","observation_id":"47592783-320f-405d-ae43-5d6cc7f4dfc6","resolution":{"observed_at":"2026-08-15T22:21:22.779592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.757087Z","title":"Intro- ducing the recola multimodal corpus of remote collaborative and affective inter- actions","venue":null,"work_id":"cfdd2bf6-eda7-4a95-9c2d-1aad8565ee44","year":2013},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.388896Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:fb0ebb4c9d4d0ea6bd58f44747b0348b2ee68261a1ed25157921bbca6179e070","observation_id":"7f090409-dd0c-4eb5-9704-86f1d03f93c0","resolution":{"observed_at":"2026-08-15T22:21:22.762355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01782","last_updated":"2022-08-02T12:13:49Z","snapshot_observed_at":"2026-08-16T17:03:18.320657Z","submitted_at":"2022-05-02T03:38:00Z","title":"Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01782","snapshot_observed_at":"2026-08-15T22:21:22.394270Z","title":"Learn- ing multi-dimensional edge feature-based au relation graph for facial action unit recognition.arXiv preprint arXiv:2205.01782, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.394270Z"},"links":{"cited_paper":"/paper/2205.01782","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:bf3743feda9b96752e6e0058a643e3d731f54cb7851acfed306daf9557cbebb6","observation_id":"a72b0733-f37f-494b-baee-f65dae840b3c","resolution":{"observed_at":"2026-08-15T22:21:22.394270Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12482","last_updated":"2022-11-19T18:42:55Z","snapshot_observed_at":"2026-08-16T16:14:52.198148Z","submitted_at":"2022-11-19T18:42:55Z","title":"GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge Features","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12482","snapshot_observed_at":"2026-08-15T22:21:22.399827Z","title":"Gratis: Deep learning graph representation with task-specific topology and multi-dimensional edge fea- tures.arXiv preprint arXiv:2211.12482, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.399827Z"},"links":{"cited_paper":"/paper/2211.12482","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:682bf5ecb8649e7892e61f4eb477d140f99130a89e700a4429837b9983339626","observation_id":"0501fc19-f19f-45f3-acfb-2766aa825c2e","resolution":{"observed_at":"2026-08-15T22:21:22.399827Z","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":"2026-08-15T22:21:22.737478Z","title":"Estimation of continuous valence and arousal levels from faces in natural- istic conditions.Nature Machine Intelligence, 3(1):42–50, 2021","venue":null,"work_id":"c9cb16db-b1e9-4477-81b8-2f3a52bac2bf","year":2021},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.405102Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:c2b11dda946d32aa6a55df2fcd5751f8b26ca5995284f8dc425427d3e7039668","observation_id":"336e6d6a-4068-420e-91cc-68722152151f","resolution":{"observed_at":"2026-08-15T22:21:22.745196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.718102Z","title":"Teach: Temporal action composition for 3d humans","venue":null,"work_id":"27ab4f37-76ac-4abb-8e49-aa8126e42ae8","year":2022},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.410163Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:10e02ce7dab6e2ae2f78412b405026ff44195b28b7bfcdfb245bc1d42ec29176","observation_id":"3c5609f6-896b-4781-a43e-6f768feebc67","resolution":{"observed_at":"2026-08-15T22:21:22.724417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-15T22:21:22.696009Z","title":"Belfusion: Latent diffusion for behavior-driven human motion prediction","venue":null,"work_id":"94cc240c-fb68-45ca-a4ff-c254816331b3","year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.415261Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:a62a49b7f88f03729e6da7d4eb5e6138dcb3e6ba67c8919f10381f33d7b53308","observation_id":"bc1b836f-60d4-441e-8733-4f9c5fc6a87c","resolution":{"observed_at":"2026-08-15T22:21:22.703091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.15505","last_updated":"2023-10-12T07:55:05Z","snapshot_observed_at":"2026-07-06T16:24:17.829828Z","submitted_at":"2023-09-27T09:13:40Z","title":"Finite Scalar Quantization: VQ-VAE Made Simple","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.15505","snapshot_observed_at":"2026-08-15T22:21:22.420276Z","title":"Finite scalar quantization: Vq-vae made simple.arXiv preprint arXiv:2309.15505, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.420276Z"},"links":{"cited_paper":"/paper/2309.15505","citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:f12814173d55815ea9a36da5b4e212e0bdd352ce806b1a6864c62409836e13fd","observation_id":"907748d3-ca60-427a-ac94-98b628617a40","resolution":{"observed_at":"2026-08-15T22:21:22.420276Z","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":"2026-08-15T22:21:22.425997Z","title":"Pytorch: An imperative style, high-performance deep learning library.Advances in neural information processing systems, 32, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.425997Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:72a2efff39f204560e4205742777f0a3a40932c277603bff827930e8c4bb2126","observation_id":"b01912c6-e0d7-429e-a112-7475e124f912","resolution":{"observed_at":"2026-08-15T22:21:22.425997Z","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":"2026-08-15T22:21:22.431689Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.431689Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:960b58d95931cd935c060b3f3e78b9f78a05c07ce94d3fd6edfd37d35fc514cd","observation_id":"2fc365fd-cbc8-4bd5-8a10-87f7a49cf3a0","resolution":{"observed_at":"2026-08-15T22:21:22.431689Z","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":"2026-08-15T22:21:22.437617Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.437617Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:1a3baf3b8c3e3a1a3b1b9bf8a4fb300f2c1d52a3890244b4244d5e070649152d","observation_id":"637225b1-a717-4d60-a231-7adbd3ee4ac2","resolution":{"observed_at":"2026-08-15T22:21:22.437617Z","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":"2026-08-15T22:21:22.443646Z","title":"Pirenderer: Control- lable portrait image generation via semantic neural rendering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-15T22:21:22.443646Z"},"links":{"citing_paper":"/paper/2505.07901"},"observation_digest":"sha256:2b019fa44618a1b8ac2b642253f237078a6bc6fa3ff4741d835da388eadc0ba9","observation_id":"033874c0-2649-4076-8a03-41084606f91c","resolution":{"observed_at":"2026-08-15T22:21:22.443646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.07901","last_updated":"2025-05-12T09:22:27Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T22:15:43.977279Z","submitted_at":"2025-05-12T09:22:27Z","title":"Latent Behavior Diffusion for Sequential Reaction Generation in Dyadic Setting"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":1,"verified_fuzzy":26},"total_outbound_references":43},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.07901."}