{"as_of":"2026-08-18T06:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9c02d64b797f84c5d9411f4960dc7697f08e6643d46042345cf91469d9e4a646","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:14:36.420554Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T08:40:51.554150Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.08493","snapshot_observed_at":"2026-07-11T18:34:29.549966Z","title":"Context-aware tfl: A universal context-aware contrastive learning framework for temporal forgery lo- calization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04498","last_updated":"2026-07-26T17:52:57Z","snapshot_observed_at":"2026-08-13T08:45:09.652372Z","submitted_at":"2026-07-05T20:51:24Z","title":"UniSkip-Mamba: A Frequency-Aware State Space Model for Audio-Visual Temporal Forgery Localization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T18:34:29.549966Z"},"links":{"cited_paper":"/paper/2506.08493","citing_paper":"/paper/2607.04498"},"observation_digest":"sha256:4c4c729bf902ff2e98e67184377d5203b53f1158871cadfc57e30e063af424eb","observation_id":"0d1ab653-4e8a-4612-95b3-fd652a5f02c6","resolution":{"observed_at":"2026-07-11T18:34:29.549966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.08493","snapshot_observed_at":"2026-08-02T08:40:51.554150Z","title":"Context-aware tfl: A universal context-aware contrastive learning framework for temporal forgery lo- calization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04498","last_updated":"2026-07-26T17:52:57Z","snapshot_observed_at":"2026-08-13T08:45:09.652372Z","submitted_at":"2026-07-05T20:51:24Z","title":"UniSkip-Mamba: A Frequency-Aware State Space Model for Audio-Visual Temporal Forgery Localization","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T08:40:51.554150Z"},"links":{"cited_paper":"/paper/2506.08493","citing_paper":"/paper/2607.04498"},"observation_digest":"sha256:4994b00282e6bda00b923c4a7a27092698e67503684b8156cbcc0d655f0dc68a","observation_id":"9bbae765-f38c-4904-b766-81eee8c685c2","resolution":{"observed_at":"2026-08-02T08:40:51.554150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.08493/citation-record","integrity":"/paper/2506.08493/integrity","json":"/paper/2506.08493/citation-record.json","paper":"/paper/2506.08493"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:14:36.921570Z","title":"Audio multi-view spoofing detection framework based on audio-text-emotion correlations,","venue":null,"work_id":"76195e9d-39ae-4634-81e7-53b0ae0cc014","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.241089Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:397e2ae727f1fa12bc62292bbf54bdccc10ac715012fcb08fdf5ad3f754c03d3","observation_id":"7d3a8f7b-396a-4f94-8ff5-590e41f3a0eb","resolution":{"observed_at":"2026-08-07T05:14:36.924777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.912307Z","title":"Learning from yourself: A self-distillation method for fake speech detection,","venue":null,"work_id":"aa313fd1-70ff-42b6-a71a-a4156e396da5","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.244885Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:c098c2958e895c9b9fbb8dc19a08239fb5b2cfeba9bc9d797dcf1e6bf71db669","observation_id":"50b95873-cc68-499f-9633-334373593996","resolution":{"observed_at":"2026-08-07T05:14:36.916202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.902606Z","title":"Dynamic difference learning with spatio-temporal correlation for deepfake video detection,","venue":null,"work_id":"56ee2184-a57e-4c6a-acd2-f85ef061bd33","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.248251Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:aac9b094111de59f831ed8d972990f108cd0b5cf59e260756dc3b538ec8dc536","observation_id":"905328f0-e401-4a30-a696-0cda347cfae9","resolution":{"observed_at":"2026-08-07T05:14:36.906244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.893349Z","title":"Deepfake detection via inter-frame inconsistency recomposition and enhancement,","venue":null,"work_id":"f884a98e-def1-4186-bcc2-efc99f7ea0d6","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.251756Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:c41fe7ae96a06f3a06341efca03b6503686fb2c7d46130e385affecd118d3a75","observation_id":"c61ca414-f5cf-4631-9979-b7a6fe5973a3","resolution":{"observed_at":"2026-08-07T05:14:36.896841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.883687Z","title":"Where deepfakes gaze at? spatial-temporal gaze inconsistency analysis for video face forgery detection,","venue":null,"work_id":"647719c9-9e01-4dab-a777-587eb7329245","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.255278Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:e0ffcd45bdc7717af940fb9f9a0d489aa9ada887cd628f7c170ced3f43c5c0e0","observation_id":"7d961f44-c628-4ec1-811e-99e17c40e413","resolution":{"observed_at":"2026-08-07T05:14:36.887595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.872736Z","title":"Semantic contextualization of face forgery: A new definition, dataset, and detection method,","venue":null,"work_id":"a5c0687a-6f2b-445b-bc2f-490d3f0dc9c1","year":2025},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.258259Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:a64c56e5f04176314d020b065ec84ee9d4b31ff60207ea5748ee0613717ea5c1","observation_id":"faae575d-cb2e-49fe-8c61-7adfed814f84","resolution":{"observed_at":"2026-08-07T05:14:36.877203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.862665Z","title":"Fine- grained multimodal deepfake classification via heterogeneous graphs,","venue":null,"work_id":"6b1788e2-de7a-42d2-aeea-3e4c420bdc3b","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.261572Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:9fea488ceae2aff06e3223dea3a026cdffbadba3c91e9dd93012d57340fd0abd","observation_id":"a5f714d2-5a1b-48e4-a212-298cecc22716","resolution":{"observed_at":"2026-08-07T05:14:36.866232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.851818Z","title":"Avoid-df: Audio-visual joint learning for detecting deepfake,","venue":null,"work_id":"e468c26e-f33b-4b6b-bc1d-368774e18002","year":2015},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.264599Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:0ab183ddb303f157113d623dcfd719987ced216753123979f8b935a8f0498e5e","observation_id":"ce2354e4-06d6-4a18-b55a-c6d56d6d6995","resolution":{"observed_at":"2026-08-07T05:14:36.855030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01979","last_updated":"2023-07-16T07:03:45Z","snapshot_observed_at":"2026-08-16T15:36:02.437119Z","submitted_at":"2023-05-03T08:48:45Z","title":"Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localization","version":3},"cited_work":{"arxiv_id":"2305.01979","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.01979","snapshot_observed_at":"2026-08-07T05:14:36.484118Z","title":"Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localization","venue":"cs.CV","work_id":"a18fc674-d84d-46b0-9b97-15f07f3ff1ee","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.267942Z"},"links":{"cited_paper":"/paper/2305.01979","citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:333afbd782e8acf56b2d4869fd11c73476b8ebb7967263fb2e5f878e9d46f6ce","observation_id":"12bdb277-7b28-41be-9249-089e5c860de5","resolution":{"observed_at":"2026-08-07T05:14:36.489545Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.841581Z","title":"Not made for each other-audio-visual dissonance-based deepfake detection and local- ization,","venue":null,"work_id":"09c89b8f-19d3-49b2-a530-bb1cc3656b3f","year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.271429Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:dd52ce08c8749f06e9ecbd66a91573aa2f516045e6cba72c2e4f6f253bc79a79","observation_id":"1c9ab9ed-f016-45f5-9642-dce7c9b1e199","resolution":{"observed_at":"2026-08-07T05:14:36.844911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.830519Z","title":"Audio-visual temporal forgery de- tection using embedding-level fusion and multi-dimensional contrastive loss,","venue":null,"work_id":"69beec9a-bcc6-425e-9c92-81210742337e","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.274427Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:fdac8bcab703790ba8c423731bc199ebd337deb46086851c1dc94b687aa4bd2b","observation_id":"8da9e98b-6136-4c2d-a11d-be705587b28f","resolution":{"observed_at":"2026-08-07T05:14:36.834963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.10193","last_updated":"2025-04-11T06:56:20Z","snapshot_observed_at":"2026-08-16T06:10:19.133076Z","submitted_at":"2024-11-15T13:47:33Z","title":"DiMoDif: Discourse Modality-information Differentiation for Audio-visual Deepfake Detection and Localization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.10193","snapshot_observed_at":"2026-08-07T05:14:36.277635Z","title":"Dimodif: Discourse modality- information differentiation for audio-visual deepfake detection and lo- calization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.277635Z"},"links":{"cited_paper":"/paper/2411.10193","citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:c2b419b39d895021ce74d7d57ed2ffaf3c6b40e5aa89be8c661350e1ec6de2ef","observation_id":"a89fe335-7651-4d5e-a693-ba01739559a8","resolution":{"observed_at":"2026-08-07T05:14:36.277635Z","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":"2026-08-07T05:14:36.821286Z","title":"Um- maformer: A universal multimodal-adaptive transformer framework for temporal forgery localization,","venue":null,"work_id":"30cd0093-0315-4810-87aa-2f0fcb6e049c","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.281047Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:bbddbee54bc9e9cc1052ccfcd6bcfad8fd45bc7034184d3a18c93c468fc2ea63","observation_id":"e9868303-7c6c-4790-92ee-746e12daac01","resolution":{"observed_at":"2026-08-07T05:14:36.824867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.811794Z","title":"Mfms: Learning modality-fused and modality- specific features for deepfake detection and localization tasks,","venue":null,"work_id":"0f5ee0b3-9094-4312-a145-bf786de060fe","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.283962Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:f30e47c2f274c3403315a4b11b96991bee6828ed5202507d2651cb4463f3b448","observation_id":"7714478a-1bc6-46bb-af04-3bdb7af3eba2","resolution":{"observed_at":"2026-08-07T05:14:36.815342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.286833Z","title":"Attention is not all you need: Pure attention loses rank doubly exponentially with depth,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.286833Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:94d2ff57cae77691be983c33fe4d6d9b9d3f5541864142e04f41b05ad1fb1fa2","observation_id":"4cdb5edf-c890-4ae2-ab22-4c4b53d62ab3","resolution":{"observed_at":"2026-08-07T05:14:36.286833Z","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":"2026-08-07T05:14:36.796247Z","title":"Av-deepfake1m: A large-scale llm-driven audio- visual deepfake dataset,","venue":null,"work_id":"ca580206-8fa6-4617-aa71-c7b4560ce034","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.289876Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:95c90497bd31cc63e0d5731d8e6a902090902cb6127d8617504a97b9a10dc196","observation_id":"1bf1a814-8b2c-4d79-8c8e-e238f07e20fa","resolution":{"observed_at":"2026-08-07T05:14:36.800416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.03617","last_updated":"2023-12-16T02:17:19Z","snapshot_observed_at":"2026-08-16T18:33:04.332513Z","submitted_at":"2021-04-08T08:57:13Z","title":"Half-Truth: A Partially Fake Audio Detection Dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03617","snapshot_observed_at":"2026-08-07T05:14:36.292682Z","title":"Half-truth: A partially fake audio detection dataset,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.292682Z"},"links":{"cited_paper":"/paper/2104.03617","citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:7f87be604ef4cbebeb053d51b530801703133798367685abfa67b3227ef3e59c","observation_id":"45c0f527-4640-4daa-a74a-d598375e3bd3","resolution":{"observed_at":"2026-08-07T05:14:36.292682Z","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":"2026-08-07T05:14:36.787292Z","title":"Localizing fake segments in speech,","venue":null,"work_id":"d483a8ae-d53f-4758-ae79-1b8b29c86739","year":2022},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.296001Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:686427ad573e11d0b58372c6fd64d992ab3a2975d68a05dd4fcefcc118e3cc40","observation_id":"381bf6f8-3303-4dcc-9740-278921d9b175","resolution":{"observed_at":"2026-08-07T05:14:36.791036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.778409Z","title":"Emotions don’t lie: An audio-visual deepfake detection method using affective cues,","venue":null,"work_id":"d3055542-5b15-4513-9500-4c3fed457c6d","year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.298815Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:014c47b362125b375a1284234f562cd7646aa3fffcd3a98d394edfeb32d3455e","observation_id":"6c4af9cb-f029-4b12-a3ce-6cf2811492a9","resolution":{"observed_at":"2026-08-07T05:14:36.781671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.769394Z","title":"Multimodal forgery detection using ensemble learning,","venue":null,"work_id":"3be2421e-a310-46b5-9bb1-4a72db7e0b70","year":2022},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.302418Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:97ffc5f9b18ed27244ea15dc24f2ac40500492c38881132cceb11dd2885548a9","observation_id":"e0845b8d-a937-4076-9228-144aba32dbdf","resolution":{"observed_at":"2026-08-07T05:14:36.772552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.760256Z","title":"Using graph neural networks to improve generalization capability of the models for deepfake detection,","venue":null,"work_id":"b9e0d6df-bed6-4d31-a259-a720cb9cfd2b","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.305185Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:86437ba14c418fae2cb722d0c0a963c1fd3b297b42cc597078a8a121070b4b15","observation_id":"6430d2b0-11c4-4aa6-9cbf-63a6fbd8b1f0","resolution":{"observed_at":"2026-08-07T05:14:36.763912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.750863Z","title":"Joint audio-visual deepfake detection,","venue":null,"work_id":"9f40b51e-ea1a-4ec8-9999-e3db81c96ad1","year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.308723Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:1552635db78acef279eb3110cac2bbe2ad3a469e4e48c54019c93b329d6e0442","observation_id":"781da907-9259-450b-a95e-6529c91df66a","resolution":{"observed_at":"2026-08-07T05:14:36.754444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.740858Z","title":"Avfakenet: A unified end-to-end dense swin transformer deep learning model for audio–visual deepfakes detection,","venue":null,"work_id":"d2f3deab-deed-4e37-93ad-4756269bd029","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.311278Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:dfb1bf1dc5c6b37a013d9e8f8d1b4b7d2a3f6b26e2331ed85cb0f5ef6c7c0d60","observation_id":"a2023744-ede5-487b-b50b-9a3eaf505d87","resolution":{"observed_at":"2026-08-07T05:14:36.744500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.731225Z","title":"Audio-visual person-of-interest deepfake detection,","venue":null,"work_id":"4b9ff181-6349-44b5-9eba-e7ec933c479c","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.314372Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:37d30475086518033ac2da30afacbe2b066fd066e96563e2662f585dcc5027d9","observation_id":"df9bda77-f887-4f64-8dcc-42f043961fc6","resolution":{"observed_at":"2026-08-07T05:14:36.734486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.722023Z","title":"Contextloc++: A unified context model for temporal action localization,","venue":null,"work_id":"0a61a0be-9a3a-4143-a636-db0a342d96d9","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.317299Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:1f74d56c441f6d9663075507ee780f967ee52e6c7cd1e223a7ff91d02576c7f3","observation_id":"49f301c9-29e8-4f14-8826-27b13bf57e8c","resolution":{"observed_at":"2026-08-07T05:14:36.725279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.711756Z","title":"Deep learning-based action detection in untrimmed videos: A survey,","venue":null,"work_id":"ba0bfba8-22db-45a5-994b-f960c9438096","year":2022},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.320485Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:5137f0c49c0105df3cc58a96b19c10d107470b2845d6930281764c306d0a7c51","observation_id":"6c68e50f-8a74-4c95-a880-497fa3e88137","resolution":{"observed_at":"2026-08-07T05:14:36.715990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.702339Z","title":"Semantic and temporal contextual correlation learning for weakly-supervised temporal action localization,","venue":null,"work_id":"8481ca4f-113c-422d-b74f-13bb08d2c852","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.323536Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:471ef73507cb55d56fe488b6030c7176bedf6d0045da13c196a7b2aa64008dda","observation_id":"ee908738-0d14-4ee3-a940-c3ac9476b333","resolution":{"observed_at":"2026-08-07T05:14:36.705788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.692872Z","title":"Gaussian temporal awareness networks for action localization,","venue":null,"work_id":"990e0533-9918-44f0-8a83-06fefeeb8cee","year":2019},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.326787Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:a80a66f7d5a485182e42984f547e7fbe1a6224fd17884be5c6cee05e92c51cbd","observation_id":"91156095-b0c3-4695-a932-0092dd4da528","resolution":{"observed_at":"2026-08-07T05:14:36.696343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.683167Z","title":"Mid-level fusion for end-to-end temporal activity detection in untrimmed video","venue":null,"work_id":"8e1691ea-762e-4d67-b891-9a77411d7658","year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.330081Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:8ea78dafe9ed14e7348ad5d9eaebdeafa9afd03bcc65495555ee7402e95371b8","observation_id":"f5dc23e9-5642-4e22-be1d-81aeeb838c60","resolution":{"observed_at":"2026-08-07T05:14:36.686641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.672726Z","title":"R-c3d: Region convolutional 3d network for temporal activity detection,","venue":null,"work_id":"37d6bd2a-55a6-4fd6-ba50-3929d9533bbb","year":2017},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.333161Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:a8b8d15d454a7c4916302982a6ae528bcb63e49114867c9bf5b862c3c019136f","observation_id":"fe1b953b-2b15-4382-a142-5d8ac1cf5630","resolution":{"observed_at":"2026-08-07T05:14:36.676911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.661475Z","title":"Rethinking the faster r-cnn architecture for temporal action localization,","venue":null,"work_id":"ee4baf9d-e4f9-4413-a427-39870f240da6","year":2018},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.337343Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:0a436ca9b11ad704b96a21fea53621c9ea2a199f581690f3dbea69d32f75582f","observation_id":"63244e45-be92-43b0-886a-60508bfeada7","resolution":{"observed_at":"2026-08-07T05:14:36.665388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.650797Z","title":"Graph attention based proposal 3d convnets for action detection,","venue":null,"work_id":"68df0a36-544e-46de-aa37-48ec3c7bdab7","year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.340509Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:fc9dbf774672cd225c30f3625e79a9d8ae0fe29b85d9af55e1901a171252c596","observation_id":"9875b8d3-9ac7-4609-b423-274a60877ae1","resolution":{"observed_at":"2026-08-07T05:14:36.654460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.638954Z","title":"Bsn: Boundary sensitive network for temporal action proposal generation,","venue":null,"work_id":"3d9ee788-2ceb-4890-9ac0-b24cd0d7e496","year":2018},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.344043Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:3e76cdc0f755281a0311e75413623968cd81c882397b305a2c9fc599101bb2ef","observation_id":"b9fb1b56-cb77-4482-99be-4732883a3d09","resolution":{"observed_at":"2026-08-07T05:14:36.642857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.347321Z","title":"Bmn: Boundary-matching network for temporal action proposal generation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.347321Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:4eda5230e762aea5b4688571ed32a7a2b473c33f9d558fd2ffeb05c7d4c270e4","observation_id":"744a9a04-3eeb-461e-9aac-2a700debae43","resolution":{"observed_at":"2026-08-07T05:14:36.347321Z","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":"2026-08-07T05:14:36.350440Z","title":"Actionformer: Localizing moments of actions with transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.350440Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:d5ee711fbbea833bc78c601dd042612b6ea325a86b84dcc30b1e9bf25d91d1d2","observation_id":"624f1721-18fa-438e-964d-b660e7359a63","resolution":{"observed_at":"2026-08-07T05:14:36.350440Z","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":"2026-08-07T05:14:36.354463Z","title":"Tridet: Temporal action detection with relative boundary modeling,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.354463Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:4b7739579c1ee4155cb29d77d9c8624ff6057addb021ac6dbd60c4ce20139a6e","observation_id":"41a922b9-873a-42bf-a0fb-728178bbbd84","resolution":{"observed_at":"2026-08-07T05:14:36.354463Z","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":"2026-08-07T05:14:36.611822Z","title":"Temporal action localization in the deep learning era: A survey,","venue":null,"work_id":"fc3ef2c0-e23f-4410-b6c2-3924510acd00","year":2023},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.357469Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:3c8fa3a91d5a81cf1dba78a580744a91a4f7d82ed3f5bc888305a115648eca8d","observation_id":"1fa4ae62-0ce1-4ce3-bb21-1d256f70ab2c","resolution":{"observed_at":"2026-08-07T05:14:36.616423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.360588Z","title":"A simple framework for contrastive learning of visual representations,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.360588Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:44cf97eeaea53a3e9c665b4d4b850a779f2990f65fcdf6149015b0b4cceb2a5b","observation_id":"d721b690-9d84-4833-8467-8a15718b060d","resolution":{"observed_at":"2026-08-07T05:14:36.360588Z","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":"2026-08-07T05:14:36.364461Z","title":"Exploring simple siamese representation learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.364461Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:e41baca4edbdd76639b7cd47e76ffe3166ce0b4166fc19cc85df42437e5ac91d","observation_id":"61b15b56-d8c7-4f48-b4c8-a6a0c12e8911","resolution":{"observed_at":"2026-08-07T05:14:36.364461Z","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":"2026-08-07T05:14:36.367706Z","title":"Momentum contrast for unsupervised visual representation learning,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.367706Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:e0335ab1fae51cac062c0daeaa890b914ac7d05f57ef839685b7aa6fc21e5205","observation_id":"fd3ca517-c649-4285-9530-a66a26341010","resolution":{"observed_at":"2026-08-07T05:14:36.367706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-08-14T18:53:38.574749Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-08-07T05:14:36.370808Z","title":"Representation learning with contrastive predictive coding,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.370808Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:e34a3ad0012e37a18315d046e6c47698b8f3c8064b24d62588bce297ca1f7366","observation_id":"6b4dd7ac-fa83-4345-a08d-1dfaafc223bf","resolution":{"observed_at":"2026-08-07T05:14:36.370808Z","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":"2026-08-07T05:14:36.375025Z","title":"Unsupervised feature learning via non-parametric instance discrimination,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.375025Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:1e0a1961cb45c727e7a852d3a6206c9cf7763e3c00306d34012f6425202bb78c","observation_id":"d4aa4c86-4721-4dc3-b0e6-a2e12fc01b6c","resolution":{"observed_at":"2026-08-07T05:14:36.375025Z","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":"2026-08-07T05:14:36.581040Z","title":"Fully unsupervised deepfake video detection via enhanced contrastive learning,","venue":null,"work_id":"66896480-31b6-4be2-86a1-6e4e9d82e8a6","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.378194Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:97d64b8a61a9bc77bad31d308f801c48c0d6fa221d6cb58b20a442beb2ca5694","observation_id":"d65306f1-ab22-4627-a3e8-07c80ebca915","resolution":{"observed_at":"2026-08-07T05:14:36.584578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.569279Z","title":"Frequency-aware discrim- inative feature learning supervised by single-center loss for face forgery detection,","venue":null,"work_id":"498dddef-344f-41a8-a5d2-1382de1138cc","year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.381389Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:aef106290a55fa31d9289974c126432bce4fa4db8046572dc7589259eecd6836","observation_id":"7d345e91-8944-4a31-90a3-6414e7128d89","resolution":{"observed_at":"2026-08-07T05:14:36.574510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.559511Z","title":"Dual contrastive learning for general face forgery detection,","venue":null,"work_id":"b8c2a70e-07fa-47d4-8283-133be86dc947","year":2022},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.384572Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:5ce85effdaf60288c2c5b2474638b027448b9ec7c1a885ecf9ddda0cf53f65a6","observation_id":"0f5c296e-9b82-44a0-80ed-13381dcf581f","resolution":{"observed_at":"2026-08-07T05:14:36.562933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.388668Z","title":"Supervised contrastive learn- ing,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.388668Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:c1b10701c56a6a1c2ae58b2a27fbb242e6070b092cf0d5de63d8457b3b22464e","observation_id":"e428c8a8-e02e-4fb6-ab83-74ea7a37a0b7","resolution":{"observed_at":"2026-08-07T05:14:36.388668Z","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":"2026-08-07T05:14:36.392169Z","title":"Temporal segment networks: Towards good practices for deep action recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.392169Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:955334d61c2ac6e16d644179adc31607878cd9d4135acfa087ecf808782bd98a","observation_id":"464a61a3-406b-480d-b0a4-5911c2246696","resolution":{"observed_at":"2026-08-07T05:14:36.392169Z","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":"2026-08-07T05:14:36.538151Z","title":"Quo vadis, action recognition? a new model and the kinetics dataset,","venue":null,"work_id":"42354036-c64a-41fa-b769-6073fadd8b8f","year":2017},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.396210Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:fe70ccb55f42d3238cad5c66dc2ea3b62903e60fbedc68db88e1196801ca7fd5","observation_id":"ea54a899-6f96-4329-870d-96e1f5aee266","resolution":{"observed_at":"2026-08-07T05:14:36.541857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.528717Z","title":"Byol for audio: Self-supervised learning for general-purpose audio represen- tation,","venue":null,"work_id":"a97d8793-2610-4bbe-ac07-b5d08cac14ad","year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.400020Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:5717f5e30a825a3c89b57e26cc6f4e927c79006f57ba99452ad56cdb68f74146","observation_id":"a28424ea-e652-4255-a1ef-767465922d09","resolution":{"observed_at":"2026-08-07T05:14:36.532397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-07T05:14:36.403124Z","title":"Focal loss for dense object detection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.403124Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:50b61f9f10c857916505a79bf015891dea87a9add5904e93ec04e090668dac9f","observation_id":"2fd6b2fd-c5d7-4a18-9088-c950c21cc692","resolution":{"observed_at":"2026-08-07T05:14:36.403124Z","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":"2026-08-07T05:14:36.406421Z","title":"Distance-iou loss: Faster and better learning for bounding box regression,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.406421Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:88fa10a6a141535ae74a0c61e7f559e6b3671998d6c35b80bb794735e0b57e9f","observation_id":"ed0d8098-03b6-4198-b53a-26d4d60acedc","resolution":{"observed_at":"2026-08-07T05:14:36.406421Z","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":"2026-08-07T05:14:36.410095Z","title":"Soft-nms–improving object detection with one line of code,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.410095Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:c0b11dadaffb4ef9387a50ec250562ab098b646be66f617b6d93779ae1fab411","observation_id":"da7d3222-0a85-46bb-b703-7ae9801868ef","resolution":{"observed_at":"2026-08-07T05:14:36.410095Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.14118","last_updated":"2021-10-17T17:41:25Z","snapshot_observed_at":"2026-08-16T18:14:15.524207Z","submitted_at":"2021-06-27T00:49:02Z","title":"Hear Me Out: Fusional Approaches for Audio Augmented Temporal Action Localization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.14118","snapshot_observed_at":"2026-08-07T05:14:36.413254Z","title":"Hear me out: Fusional approaches for audio augmented temporal action localization,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.413254Z"},"links":{"cited_paper":"/paper/2106.14118","citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:a98f4de6ffffaa1bbca88e89538d42fa6f6ce73d53eb46da0cd09cfb3b1c6ec1","observation_id":"3e0445ed-d735-45d9-8e5a-27832b0a8e88","resolution":{"observed_at":"2026-08-07T05:14:36.413254Z","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":"2026-08-07T05:14:36.417318Z","title":"wav2vec 2.0: A framework for self-supervised learning of speech representations,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.417318Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:77311dd03dc102a72967b575c6b6b664674c2373c136e27e2de33554da435251","observation_id":"d0553532-a118-4fbf-aec8-76f44f25fb08","resolution":{"observed_at":"2026-08-07T05:14:36.417318Z","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":"2026-08-07T05:14:36.497057Z","title":"Vigo: Audiovisual fake detection and segment localization,","venue":null,"work_id":"bf66dca4-332a-4198-992c-cd91de91544f","year":2024},"citing_paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:14:36.420554Z"},"links":{"citing_paper":"/paper/2506.08493"},"observation_digest":"sha256:d00b4be80ad00e70176771a98bc94b3683e9f76d30c8fe3ddea4ba8c8deb821f","observation_id":"b5d3541b-1920-431f-a87d-0d42e9e4c223","resolution":{"observed_at":"2026-08-07T05:14:36.501293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.08493","last_updated":"2025-06-10T06:40:43Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T06:11:04.952947Z","submitted_at":"2025-06-10T06:40:43Z","title":"Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":18,"verified_exact":0,"verified_fuzzy":36},"total_outbound_references":55},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2506.08493."}