{"as_of":"2026-08-21T06:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e6574f55b6e6833398823690b4f29b2222cce59e8760ae690dfb9b8353175934","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T00:41:44.563286Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2412.19424/citation-record","integrity":"/paper/2412.19424/integrity","json":"/paper/2412.19424/citation-record.json","paper":"/paper/2412.19424"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:41:45.572321Z","title":"Uncertainty-aware anticipation of activities","venue":null,"work_id":"b6bf7470-da74-4568-8e91-9d3422d538a5","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.287343Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:28fc41bff538e7ac90921aa759b8372896f0efec9ce0cd9d28eec38bfd59c39d","observation_id":"e092837a-7e76-4692-a52e-5b59ebd61ef0","resolution":{"observed_at":"2026-08-11T00:41:45.578371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.544427Z","title":"Long-term antic- ipation of activities with cycle consistency","venue":null,"work_id":"f522a350-04f2-4ba4-b485-f8bae7bd797b","year":2020},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.293448Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:1ee1134da5af2d8356713fe1e3f0b3717bdc5dcbba391b20ecefc92deedaec10","observation_id":"2c1e1c14-2327-4562-9d11-9817c4b5775f","resolution":{"observed_at":"2026-08-11T00:41:45.553101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.515613Z","title":"When will you do what?- anticipating temporal occurrences of activ- ities","venue":null,"work_id":"2e07651a-c549-4c26-9ed4-2ea1b366ab42","year":2018},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.298738Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:d4dae5b8db520350e2dd7ed9bcd6347150642df419a77870b874debc6ef3bac1","observation_id":"9deaaf15-856b-4487-8342-51b14e149a95","resolution":{"observed_at":"2026-08-11T00:41:45.523278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.493599Z","title":"How much temporal long-term context is needed for action segmentation? In Proceedings of the IEEE/CVF Interna- tional Conference on Computer Vision, pages 10351–10361, 2023","venue":null,"work_id":"dcb9ee4c-5e1b-425d-ae4e-41329ffa2ff5","year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.305155Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:b492ec97bddcd795d79564741a195ba36e2c195ee5858060eab70b8c0ddc196e","observation_id":"14600717-8d26-47be-a8c3-ca1e407da25f","resolution":{"observed_at":"2026-08-11T00:41:45.499053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.472102Z","title":"Unified fully and timestamp supervised tem- poral action segmentation via sequence to sequence translation","venue":null,"work_id":"8b2281dc-a3ac-467a-bad5-39c423a49193","year":2022},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.310790Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:70f71cac06c1b88bae7bf2aab035f083281dcba131746790fb2d9070406effb1","observation_id":"d95d9995-1b77-4e14-873e-7dc66acb374a","resolution":{"observed_at":"2026-08-11T00:41:45.478890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.449758Z","title":"Language models are few-shot learners","venue":null,"work_id":"db7d7def-205f-4aa4-a7a7-c9363fd3a050","year":1901},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.316983Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:4bec02a0cd0a6fa2721a27fcd8640fbdc07b22ae1de315ca9246371699420d7f","observation_id":"7846971b-5a53-4c69-8c80-cef4deffdf29","resolution":{"observed_at":"2026-08-11T00:41:45.454736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.429107Z","title":"End-to-end object detection with transformers","venue":null,"work_id":"31459b06-bb4d-471b-9572-a9aef69ac3e3","year":2020},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.324966Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:708f1962daa4e59c4df0c2421f99b035db4a051c98ae2cde07d4b39dc3e9eebd","observation_id":"8ed348f5-8e82-45b1-b479-71aef4fda0e6","resolution":{"observed_at":"2026-08-11T00:41:45.433889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.402085Z","title":"Quo vadis, action recognition? a new model and the kinetics dataset","venue":null,"work_id":"7ae2d8f7-71f9-482e-9854-a1db05f8e5bb","year":2017},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.332526Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:fdd37adf15b94802d3024a4d77b9e9cd9d709af8d42fd1bae37c8f275141129b","observation_id":"029ffbc9-b35b-4261-be8a-d90aadf9068c","resolution":{"observed_at":"2026-08-11T00:41:45.413662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.377328Z","title":"Temporal action segmentation: An analysis of modern techniques","venue":null,"work_id":"73c60836-6da7-4af8-b864-ed2512838f72","year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.337901Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:2cf720e44d7b5b252cc4d3d16a18fff77466ee818306652523828d30d00b8c55","observation_id":"db8b4f19-fc6b-4042-953d-ff2e8fec13b8","resolution":{"observed_at":"2026-08-11T00:41:45.383154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.359074Z","title":"Ms-tcn: Multi-stage temporal convolutional network for action segmentation","venue":null,"work_id":"e7c74319-c7f5-4440-af10-013e87c6cc3f","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.344618Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:2f707b32fcb25ab0b44ad6ee78b4b69406b896645ca279dd8e8c277eaa774f54","observation_id":"b079008a-cc0e-4af9-ad8c-7ff69f9aa062","resolution":{"observed_at":"2026-08-11T00:41:45.365154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.341759Z","title":null,"venue":null,"work_id":"6ded8506-153b-4092-8f95-9b7e71176886","year":1973},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.349744Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:fdb5a685a4f9c7661b033bc1c7778d0b4b20204dea997f1503399713167fc96e","observation_id":"2dd46435-7f80-457f-b66b-c474a810b420","resolution":{"observed_at":"2026-08-11T00:41:45.347176Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.324616Z","title":"Leveraging tem- poral context in low representational power regimes","venue":null,"work_id":"25482bdf-d3ef-4dd8-991c-849a7cc3836d","year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.355399Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:36f9a323103a068f4175ca56522d60afb560c10ed75872c94c528e886e1b224b","observation_id":"ae4f0d82-2c8b-4e78-9e6f-107d1a3acda1","resolution":{"observed_at":"2026-08-11T00:41:45.329513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.308060Z","title":"Forecasting future action sequences with neural mem- ory networks","venue":null,"work_id":"cd1ba4e6-d198-4705-8429-d2a19306fa91","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.362608Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:8f7d4ae1385f36e643df38766e7b3806aef7c731fc2789a6c7e0e9028d47b11f","observation_id":"dcc394ca-09e4-4460-8d16-381440b81237","resolution":{"observed_at":"2026-08-11T00:41:45.313411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.291189Z","title":"Antic- ipative video transformer","venue":null,"work_id":"e2a5bbd3-f199-43e7-a7a4-4fe6ca7169b9","year":2021},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.369604Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:8456d1099eec93fbe2579a9f04e2d465954f3315dcc535d081abe028a1c78a2f","observation_id":"532da602-f1ce-473c-b5ef-4af517d951ba","resolution":{"observed_at":"2026-08-11T00:41:45.296019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.275271Z","title":"Actionvlad: Learning spatio-temporal aggre- gation for action classification","venue":null,"work_id":"8993afe1-82a8-408e-8381-07fc9917f5ed","year":2017},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.375456Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:b6fa055bde4e87b37816f27de2ac2cedb6f6fab124bcf35112904ee4eca949ac","observation_id":"5f59b4e7-59d6-459e-a679-f248a6df5687","resolution":{"observed_at":"2026-08-11T00:41:45.280031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.256109Z","title":"Actfusion: a unified diffusion model for action segmentation and anticipation","venue":null,"work_id":"74bead9d-1cc6-4b39-9cdf-dc31abc6243d","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.380546Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:88c486100b14e74e62ac76ed4dd53b1116aa91a65bde8e902d99a441785e856e","observation_id":"6b64080e-5248-44bf-b0c1-5d76606ac5af","resolution":{"observed_at":"2026-08-11T00:41:45.263460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.232917Z","title":"Activity grammars for temporal action segmentation","venue":null,"work_id":"ee3ddc3c-e69b-4fc9-ab1c-58c209e62c5c","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.386487Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:48099c99c8cbac11b66cf050462cbdd6c8bd71f19d3d67f7b58a0025659b8060","observation_id":"a711de46-ff54-499b-b6c9-166791076050","resolution":{"observed_at":"2026-08-11T00:41:45.239070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.215540Z","title":"Future transformer for long-term action anticipation","venue":null,"work_id":"3334fa22-60e0-4732-b79b-67778c4dd8db","year":2022},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.393707Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:144ef3a35259608f40268a95b916b4c1ecaa6aca46f573b6e05932596e5ed54c","observation_id":"f04026ae-24a0-4d3b-b518-b3596cd756ee","resolution":{"observed_at":"2026-08-11T00:41:45.221287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.00942","last_updated":"2022-04-02T21:50:45Z","snapshot_observed_at":"2026-08-20T20:50:16.979375Z","submitted_at":"2022-04-02T21:50:45Z","title":"A-ACT: Action Anticipation through Cycle Transformations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.00942","snapshot_observed_at":"2026-08-11T00:41:44.400125Z","title":"A-act: Action anticipation through cycle transformations","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.400125Z"},"links":{"cited_paper":"/paper/2204.00942","citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:e0e0d383c56d2e640b01e4ec65d6a53fc0dc94f253b0e1e577fb44a256c5962b","observation_id":"e871e156-6fe5-4e81-92c2-abe6f945acb8","resolution":{"observed_at":"2026-08-11T00:41:44.400125Z","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":"2026-08-11T00:41:44.407032Z","title":"Gaussian error linear units (gelus), 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.407032Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:21a3fc34198d36490e7a1131a37612bdbd3fceffaace1a7c1a1690037fbb1715","observation_id":"7e11a56a-f0ef-40d0-9d4b-5ac69fe236a0","resolution":{"observed_at":"2026-08-11T00:41:44.407032Z","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":"2026-08-11T00:41:45.184261Z","title":"Bidi- rectional lstm-crf models for sequence tag- ging, 2015","venue":null,"work_id":"a5dd95ae-b642-4cb9-b758-b1b024d7411d","year":2015},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.412197Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:58bb586cdbf963fa193e46d20f1a9301102ac32f723f66ef210a78d694e9e163","observation_id":"f8e49a48-c2a6-4302-b2f6-99514063251c","resolution":{"observed_at":"2026-08-11T00:41:45.190687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.164827Z","title":"Timeception for complex action recognition","venue":null,"work_id":"437473a5-d70d-4fdc-a090-84451fc95138","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.417586Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:650f7cba38b7672d3f35b1893e140a5de3d48fbc8f4b1a221580a2ec8b5fde10","observation_id":"74d701c3-7f9c-4f57-917c-53d20f214c5a","resolution":{"observed_at":"2026-08-11T00:41:45.170586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.145545Z","title":"Videograph: Rec- ognizing minutes-long human activities in videos","venue":null,"work_id":"ae324c93-738c-48e8-a515-c358e40ce9da","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.423361Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:569df340f60f1a58895be9cf371ce11d9dfe54b31818af013ddacd4fb681c0c9","observation_id":"3b73664e-a7f7-4f02-aae2-28bca639a8cb","resolution":{"observed_at":"2026-08-11T00:41:45.152026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.125985Z","title":"Time-Conditioned Action Anticipation in One Shot","venue":null,"work_id":"96726b37-20e4-4a02-bb90-92128486ac52","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.428431Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:69f68b87301366872a9f1ec1a0468640cdf2bbb0f85aa70e38d408c231ba22da","observation_id":"b9829dd2-932f-42ff-89bd-0f39c3dd4d9e","resolution":{"observed_at":"2026-08-11T00:41:45.131478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.108885Z","title":"Palm: Predicting actions through language models, 2024","venue":null,"work_id":"ab524599-194c-49c0-97c5-2604a60f587b","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.432934Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:4076c010a0ea84b4c78a5511b3fa420168e47a0862c222abf3308fd287ed684b","observation_id":"c414e38c-c833-49da-a0c5-042112417d56","resolution":{"observed_at":"2026-08-11T00:41:45.114037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.090777Z","title":"The language of actions: Recovering the syn- tax and semantics of goal-directed human activities","venue":null,"work_id":"78580eff-4d55-4af8-9b64-8e2edaed33db","year":2014},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.437653Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:4103745663c10a55fe3387ce854ccdf286a74963cadbed526df2c3caa61bf073","observation_id":"10ffaca0-c31f-41e2-bd62-caf5f4e5299b","resolution":{"observed_at":"2026-08-11T00:41:45.095878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.070639Z","title":"An end-to-end generative framework for video segmentation and recognition","venue":null,"work_id":"5b2ad47d-8d24-457d-b237-ec1dbd236d8c","year":2016},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.443271Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:508ebfec4f18ed6edd699308fb770ae6a3f87db4c1d7716a878f028d776cb13e","observation_id":"0643354a-8968-4a2d-9cb5-0b67037fee7f","resolution":{"observed_at":"2026-08-11T00:41:45.077665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.050928Z","title":"A hybrid rnn-hmm approach for weakly supervised temporal action segmenta- tion","venue":null,"work_id":"c02083a2-4035-469e-a29f-b64ca2b8cd03","year":2018},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.448244Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:9c8d87fc3c96ea3678180c75b7bca005b10c23e5ac9c5c3019c79214d6f175b3","observation_id":"efb9df89-8786-400f-86ca-42a899dcb35f","resolution":{"observed_at":"2026-08-11T00:41:45.057356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.452331Z","title":"On information and sufficiency","venue":null,"work_id":null,"year":1951},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.452331Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:ae1fa44823d9f4fdffd87508f975d64a45f82ab929f73fde3d8abb524356e88d","observation_id":"33b8efc1-3de7-463c-81bd-9699d1446b2b","resolution":{"observed_at":"2026-08-11T00:41:44.452331Z","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":"2026-08-11T00:41:45.017845Z","title":"Conditional random fields: Probabilistic models for segmenting and labeling sequence data","venue":null,"work_id":"ebe2f41a-b041-4232-a155-8e66ca7133b2","year":2001},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.456365Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:7329f3d41da7d1be1af629b25ccf711d6da15070dd2509f5be795f38882c74be","observation_id":"0b8e9b7a-f0bf-4752-819f-9cc2230ff79c","resolution":{"observed_at":"2026-08-11T00:41:45.023224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:45.000691Z","title":"Tem- poral convolutional networks for action seg- mentation and detection","venue":null,"work_id":"894612ae-a0bb-4619-ba33-d2f95831d107","year":2017},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.460539Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:1355337e1ebe189b7e6773eaa7aa9d2468d985056aafb81d19e8535d65fccc0f","observation_id":"eec63cff-bfb9-43e2-91b3-478044d386cf","resolution":{"observed_at":"2026-08-11T00:41:45.005996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.982730Z","title":"Ms-tcn++: Multi-stage temporal convolutional network for action segmentation","venue":null,"work_id":"2cba6575-ec5d-48bc-89c1-81c0f0d4c898","year":2020},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.464726Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:e8c047ac8a5d5f0d7bf74eabad1255a60300cb4aa96d44839fa200f7285388ac","observation_id":"4a2db1fc-a99c-4706-b41f-64cfbb562864","resolution":{"observed_at":"2026-08-11T00:41:44.987956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.965687Z","title":"In the eye of beholder: Joint learning of gaze and actions in first person video","venue":null,"work_id":"7c072277-2617-4d58-a983-198fa5a49c38","year":2018},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.468966Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:a691eeacb74f3ec06a7cfd5add65a26efad4cbdb9114415f527d74d819ac60fc","observation_id":"03153bad-ad38-447a-a327-2242d7184a76","resolution":{"observed_at":"2026-08-11T00:41:44.970836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.950603Z","title":"SGDR: stochastic gradient descent with warm restarts","venue":null,"work_id":"1df1f6f3-6bff-4585-b723-5c43d73380af","year":2017},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.473280Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:582fac809cdc821e568bcae21c7dddede4960851f15d074acd554cdd69f863f1","observation_id":"704f479d-99d8-46a6-907b-5d3cf066bdab","resolution":{"observed_at":"2026-08-11T00:41:44.955170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.934833Z","title":"Decou- pled weight decay regularization","venue":null,"work_id":"aaa4710a-bbec-469d-8bcf-88d0f190051a","year":2019},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.477339Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:1f530b34ae0f4d184f24b555d2e135b97c96e3eaaf234a45ba9a40fdb43b3432","observation_id":"0869ca5a-e0bd-4fdb-881a-ec798b96c399","resolution":{"observed_at":"2026-08-11T00:41:44.939915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.913991Z","title":"Fact: Frame- action cross-attention temporal modeling for efficient action segmentation","venue":null,"work_id":"1a4cb652-cdd7-462b-ac7d-8a7779909913","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.481556Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:687d695ade34157e12869845fb1359f2dbd4195000b1636dd2de8d0e7c4b1a0b","observation_id":"dd52dc1d-6e7d-41a2-a673-6c92c50d0594","resolution":{"observed_at":"2026-08-11T00:41:44.920916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.890206Z","title":"End- to-end fine-grained action segmentation and recognition using conditional random field 12 models and discriminative sparse coding","venue":null,"work_id":"22753d73-6c0f-4757-b011-5503ee1db93f","year":2018},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.485631Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:a97caaecb15956e7bb2f78b5c9af6fd7a12556c4104f8d5f307733b47394f2f0","observation_id":"91a887f5-acd1-4087-a6d1-b64c9b8a094c","resolution":{"observed_at":"2026-08-11T00:41:44.895182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.871211Z","title":"Can’t make an omelette without breaking some eggs: Plau- sible action anticipation using large video- language models","venue":null,"work_id":"9f8df11e-8c0f-413e-9d7e-ce41f1ad1a8d","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.490401Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:4915bde4c4f5382a758e3c8dd2ed25a29abbe33202e57a3e71e9388346632283","observation_id":"18b08921-636c-4619-9c88-973d9523a876","resolution":{"observed_at":"2026-08-11T00:41:44.876945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.853091Z","title":"Ego- topo: Environment affordances from egocen- tric video","venue":null,"work_id":"bddb3033-dbf6-4fbb-835c-c4a1a24937c7","year":2020},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.495028Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:06db99b6c6ccfdb69be3d089d08cab220195d9cb0a54340c98f9bf2fc8ee868a","observation_id":"f5bf084d-2c82-400f-832b-a33a6efb0198","resolution":{"observed_at":"2026-08-11T00:41:44.858848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.833857Z","title":"Rethinking learning approaches for long-term action anticipation","venue":null,"work_id":"2c8b179f-bfec-4d0c-9478-3328d7fbb26b","year":2022},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.499787Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:add558abad52e0991019fcf4e6d05edc86b09ecea7be97807edf964333bb3c27","observation_id":"f6e98bb8-d7bd-41d5-87b6-2148a59ae2e0","resolution":{"observed_at":"2026-08-11T00:41:44.839612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.812226Z","title":"Temporal aggregate representations for long-range video understanding","venue":null,"work_id":"38228acc-0470-460e-8128-52c401af62df","year":2020},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.504749Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:7ec8898b245da073d8665c0cb0970ba5ded3b4e6db1a799147edf304656351bd","observation_id":"9c7e165f-dca1-4d6b-b339-6c9d7a75d381","resolution":{"observed_at":"2026-08-11T00:41:44.817566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.795323Z","title":"Combining embedded accelerometers with computer vision for recognizing food prepa- ration activities","venue":null,"work_id":"693a8abf-76d0-4429-b01d-243bd325cffe","year":2013},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.509651Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:ba05611f924545c3fd9b7bb7ac2664f15720f3f54cc3fa899b9a893cab848018","observation_id":"1972f7b0-c658-4dba-8fb3-46e62c5fdc93","resolution":{"observed_at":"2026-08-11T00:41:44.800692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.776884Z","title":"Attention is all you need","venue":null,"work_id":"3f1656fc-74e8-4ecc-a63b-d330d2e7468b","year":2017},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.514757Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:7c7450b8f94910662c286a6b26748b55fbf5c5727da29e24b052d66336655e1f","observation_id":"aef2ace7-6939-4bf0-9a42-700c415f218d","resolution":{"observed_at":"2026-08-11T00:41:44.782319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.758624Z","title":"Vamos: Versatile action models for video understanding","venue":null,"work_id":"dc1e30a4-67d8-4fa5-9fd8-189a94f52a95","year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.521396Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:9dbe1fe6f777859849b6a1543edb3af5bf3239c0b34335540a228c28318e2cce","observation_id":"54b06b13-cac6-49c3-878d-69e292090c1e","resolution":{"observed_at":"2026-08-11T00:41:44.763934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.740157Z","title":"Don’t pour cereal into coffee: Differentiable temporal logic for temporal action segmen- tation","venue":null,"work_id":"c51e88b5-4f2b-4b70-b786-06c0d8e8f2fc","year":2022},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.527932Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:65a5e88e7362fec945e33bdf13da3a666820120a301f767dd7461c6ee0bb3497","observation_id":"93931b65-cf84-4b06-8e03-0f4ba4193305","resolution":{"observed_at":"2026-08-11T00:41:44.746095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.719951Z","title":"Gated temporal diffusion for stochastic long-term dense anticipation","venue":null,"work_id":"f93813dd-a82a-48f4-ba78-acb2193e14ba","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.533162Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:54fc67c14cc1d4027e6116ce4c32890e9020c4d3452249576688e26c2b35b755","observation_id":"76d0ed98-6a52-4837-b5dd-a9ac31d582dc","resolution":{"observed_at":"2026-08-11T00:41:44.726533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.700655Z","title":"Object-centric video represen- tation for long-term action anticipation","venue":null,"work_id":"2bd436dd-2fff-4c39-b4b6-72a56873b4f5","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.538129Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:50647aaccbcf909f5d72225ccdef7cc785bc376fbfa1f10b76a8814f4f40b81e","observation_id":"553358cf-bb57-465a-a15c-81bcc282e6b2","resolution":{"observed_at":"2026-08-11T00:41:44.705796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.683827Z","title":"On diverse asynchronous activity anticipation","venue":null,"work_id":"dd94f9b1-5528-4847-accb-b6a6b8f993dd","year":2020},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.543312Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:775c4187862e625fbeda4bf19b90310d6253a458f358e938f498ab2bd90a4198","observation_id":"3d52cdc8-00c6-4359-9afa-a9f5ff6b594f","resolution":{"observed_at":"2026-08-11T00:41:44.688535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.667447Z","title":"Antgpt: Can large language models help long-term action antic- ipation from videos?, 2024","venue":null,"work_id":"35728056-b436-427a-ab60-c702d09587bb","year":2024},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.547876Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:0f102da14395ff5fc4ddccda8211fdad963b204962466af855837caa83adebf2","observation_id":"90365dab-21b5-4211-8cc9-ea1f4998cfb9","resolution":{"observed_at":"2026-08-11T00:41:44.672547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-11T00:41:44.650830Z","title":"A sur- vey on deep learning techniques for action anticipation, 2023","venue":null,"work_id":"af6b4e23-ec62-4010-a8da-11a8058bd31f","year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.552638Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:9d68e37a3112c5053ac7c82f61c35b91d25b11f4bf6fe5e3893125964c153f66","observation_id":"27b5e351-646f-4d85-a0de-109c1737c9a2","resolution":{"observed_at":"2026-08-11T00:41:44.656417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15991","last_updated":"2023-11-27T16:40:09Z","snapshot_observed_at":"2026-08-18T18:40:23.531807Z","submitted_at":"2023-11-27T16:40:09Z","title":"DiffAnt: Diffusion Models for Action Anticipation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15991","snapshot_observed_at":"2026-08-11T00:41:44.557564Z","title":"Diffant: Diffusion mod- els for action anticipation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.557564Z"},"links":{"cited_paper":"/paper/2311.15991","citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:d93fc72620d04398338374d242f7838e6843c7c0e410f160ce618e46977b7a9c","observation_id":"af9aa929-80ea-450a-b039-d735de65c3e7","resolution":{"observed_at":"2026-08-11T00:41:44.557564Z","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":"2026-08-11T00:41:44.632763Z","title":null,"venue":null,"work_id":"ede1edd7-c79d-4f9b-a99a-2a9b2b6704ea","year":null},"citing_paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T00:41:44.563286Z"},"links":{"citing_paper":"/paper/2412.19424"},"observation_digest":"sha256:455bedfd8a6d52ea29a188cfdeed979e6b9e66168c41b7e4de48f03918b833c6","observation_id":"92ec0a4a-d670-40b1-b513-d78883715a0f","resolution":{"observed_at":"2026-08-11T00:41:44.638877Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.19424","last_updated":"2024-12-27T03:29:10Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-21T05:06:55.944693Z","submitted_at":"2024-12-27T03:29:10Z","title":"Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":46},"total_outbound_references":52},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2412.19424."}