{"as_of":"2026-08-07T10:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5af2b4d96e0bae1a29888c2678aa71a68e515997157d2a8883095ed64ea91366","coverage":[{"denominator":71,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":71,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T12:47:34.016786Z","state":"measured"},{"denominator":71,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":71,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.21530/citation-record","integrity":"/paper/2507.21530/integrity","json":"/paper/2507.21530/citation-record.json","paper":"/paper/2507.21530"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T12:47:35.846507Z","title":"High- resolution image synthesis with latent diffusion models,","venue":null,"work_id":"590a0093-0d4d-4b92-b4eb-6e87ae42ec53","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.420704Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:f41625a62d15475575ab5afc9b3cfe487065a8fb1cbb8e4cf79516373d54b4cd","observation_id":"c1ee763d-c8ac-4eab-a45d-48044c2e8401","resolution":{"observed_at":"2026-08-06T12:47:35.852552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.825102Z","title":"Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models,","venue":null,"work_id":"710787ac-2f9f-4904-a52c-ca8353f6a4fd","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.428504Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:35493010a077a432af74afda64609f5d923380e6d16d8d52e42af870965f9404","observation_id":"d321f5cf-aea9-4a2d-a864-9976f6e9d3e9","resolution":{"observed_at":"2026-08-06T12:47:35.830879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.801680Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics,","venue":null,"work_id":"72037d55-b639-4ee0-ab46-0d04e1d1f5b2","year":2015},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.439127Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:e69afe65320f36a66844ee9c8770db4b02b436aa3ef40378bb4803a2d2a99a0a","observation_id":"0a54664e-c24a-453d-b267-e581aadee842","resolution":{"observed_at":"2026-08-06T12:47:35.807211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.771714Z","title":"Dcface: Synthetic face generation with dual condition diffusion model,","venue":null,"work_id":"d7c240bb-11e0-4afc-b2fd-728d330f4e01","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.595863Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:5b327b1435546a509048019952531ac5a6a678f12ef6b0d2f10f70dfa6009569","observation_id":"5743618b-d756-4962-9f3a-7e75b33495d0","resolution":{"observed_at":"2026-08-06T12:47:35.778561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.746530Z","title":"Diffusion facial forgery detection,","venue":null,"work_id":"88b3a5f5-f0ca-46fe-96d9-3edc4e03069a","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.604643Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:14e2e683b2e7e622c1b22cca7e8a69fb8538b1f76e7a7888258cc77153ff3b49","observation_id":"de66bf47-f22d-4c90-a916-60187aea132a","resolution":{"observed_at":"2026-08-06T12:47:35.752025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.724679Z","title":"Region-aware face swapping,","venue":null,"work_id":"0b13da27-1e0c-4465-9ff4-c17e69c2e7d1","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.610199Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:6fea443d37a68bdc843d4d5f559147c6ae94f6377d93f7d6c704527541d9dcc0","observation_id":"247624d5-2b39-43b9-8739-6b4aff74b8f2","resolution":{"observed_at":"2026-08-06T12:47:35.731044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.696048Z","title":"Diffswap: High- fidelity and controllable face swapping via 3d-aware masked diffusion,","venue":null,"work_id":"fc3b2978-537c-40a4-95cc-a16c7e2964e5","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.616645Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:bfcc84530fa3b2f6cf2cc132f0e3abffd9722da15a30e5e84fe4e538e56f0ea8","observation_id":"549663f8-dcde-4105-827c-c7c0ddc44bb4","resolution":{"observed_at":"2026-08-06T12:47:35.704604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.20698","last_updated":"2025-02-28T04:15:36Z","snapshot_observed_at":"2026-08-06T04:50:39.262404Z","submitted_at":"2025-02-28T04:15:36Z","title":"Towards General Visual-Linguistic Face Forgery Detection(V2)","version":1},"cited_work":{"arxiv_id":"2502.20698","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.20698","snapshot_observed_at":"2026-08-06T12:47:34.147369Z","title":"Towards General Visual-Linguistic Face Forgery Detection(V2)","venue":"cs.CV","work_id":"aaa2e1d3-8942-4878-b5df-29584403c2a6","year":2025},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.622340Z"},"links":{"cited_paper":"/paper/2502.20698","citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:f48855ee6fe57d9f507b34ceeca79944091e359447a251f7a485cc3acbba7e42","observation_id":"2771f4bb-d7ab-4f29-92ec-e636e331430c","resolution":{"observed_at":"2026-08-06T12:47:34.153839Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.673026Z","title":"Diffusionface: Towards a comprehensive dataset for diffusion-based face forgery analysis,","venue":null,"work_id":"1ce32241-dcbb-470a-a60a-82d54b9f5701","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.627489Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:3301157000c3f978c65ebaa8cf8eef5d0303d89f0878856076aba8f70ed7153a","observation_id":"3af3aabd-9a89-4549-8dcc-c7fb2015bb17","resolution":{"observed_at":"2026-08-06T12:47:35.682030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.635973Z","title":"Can we leave deepfake data behind in training deepfake detector?","venue":null,"work_id":"336e6492-dc49-430c-8a52-14c0af459b6c","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.635688Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:52f87fca094cc9703f28ff0666350195355f591638c41aa4ee5df974df77615f","observation_id":"e0a5a68e-5061-46f9-a8f3-2f965329ed25","resolution":{"observed_at":"2026-08-06T12:47:35.651873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.615688Z","title":"Contrastive learning for deepfake classification and localization via multi-label ranking,","venue":null,"work_id":"8cbfefd5-763b-40cc-836b-48bd9130dae0","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.642405Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:3560520b1ba08f7baace5719892bec6f5a9e4dbfbaf8ea8390d03e61d883b348","observation_id":"f82a7a2b-2a38-47fd-beb8-ab0e48272a28","resolution":{"observed_at":"2026-08-06T12:47:35.621406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.574031Z","title":"Mmnet: multi- collaboration and multi-supervision network for sequential deepfake detection,","venue":null,"work_id":"b099100e-52d8-4666-8f8b-25c85392769a","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.649085Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:5c3b2b59dfa2b66468e5af27626e13704920f6928a2c2a8c51e9713962ec7e3f","observation_id":"a61e62c9-92d7-48b5-a252-32dfb26dd60a","resolution":{"observed_at":"2026-08-06T12:47:35.581070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.549368Z","title":"Generalizing deepfake video detection with plug-and-play: Video-level blending and spatiotemporal adapter tuning,","venue":null,"work_id":"fbea9fbf-a80c-42ca-a47c-cc7c96f92cf0","year":2025},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.653890Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:26f621c451c0cbb6737c6a27760aa3a5ed54e8ba667060942d124cecd28e64b0","observation_id":"5a56d8d1-f272-4d03-bf13-e26153bb401c","resolution":{"observed_at":"2026-08-06T12:47:35.556086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.522988Z","title":"Rethinking the up-sampling operations in cnn-based generative network for gener- alizable deepfake detection,","venue":null,"work_id":"3fbc2bbb-1123-49cc-adfd-4435c70a2183","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.658936Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:166814d91c6bdf99845326ed7dc8f71ebb3fdceaed041a02f605dfc843e36621","observation_id":"a58e58e8-a90a-4c01-9d35-33d1db4ac74b","resolution":{"observed_at":"2026-08-06T12:47:35.532255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.494305Z","title":"Contrastive pseudo learning for open-world deepfake attribution,","venue":null,"work_id":"c794576f-9615-4304-875f-49ed629f02ba","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.665612Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:0a0d549e0c8dd1d71295ee4c913416d06149c6255cfb70865e9c86a1439643ca","observation_id":"7a3983b5-a186-4895-a631-d5dac188ae75","resolution":{"observed_at":"2026-08-06T12:47:35.503148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.466838Z","title":"Jointly defending deepfake manipulation and adversarial attack using decoy mechanism,","venue":null,"work_id":"6a747b15-9cf3-4f4c-8eb7-e78cebe61ffe","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.672110Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:cce1b40fbf92d4c00e4bd6581be0d1d2a59ccb4cb73d0ad0ed5da4123fb19e8d","observation_id":"66fea0bf-7fbd-4c49-936d-3f704e78dcce","resolution":{"observed_at":"2026-08-06T12:47:35.472930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.446317Z","title":"Supervised anomaly detection via conditional generative adversarial network and ensemble active learning,","venue":null,"work_id":"c0235e90-6704-44e0-8997-5a1083a92f91","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.677208Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:33b0e12b08354e62ea6bcbb263a324f0227a9b3ab3ec085fe5639bd0bb8e85a7","observation_id":"8ccf16ec-b54d-4ab8-80c2-bf577eb5a842","resolution":{"observed_at":"2026-08-06T12:47:35.452240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.410552Z","title":"Faceforensics++: Learning to detect manipulated facial images,","venue":null,"work_id":"61c29d52-eece-455a-a009-faa55f5d7b03","year":2019},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.682969Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:6de25b6dc4255e0a45f9f1b97289e97110b529ae9e0d6b5e23c9d2969d85807e","observation_id":"72e2f0e4-a8d0-4ca0-98c7-84b0b8fa4965","resolution":{"observed_at":"2026-08-06T12:47:35.424998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.388130Z","title":"Thinking in frequency: Face forgery detection by mining frequency-aware clues,","venue":null,"work_id":"ebff8334-bdd1-403c-83bf-839e434e5ea0","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.688590Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:43e4898c9fbff87aebe0494cbc5b5eb3ea88db31feacf88922ad5e2539693c84","observation_id":"d50273d0-1b21-411c-b502-b2560bb7ecc7","resolution":{"observed_at":"2026-08-06T12:47:35.393821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.361022Z","title":"Multi- attentional deepfake detection,","venue":null,"work_id":"58f23afc-55dc-4534-8ce4-c0b2dfacd19d","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.693232Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:315a7228274a841e9e3e35da57fd9a6ea81d03bd3c00ea309597ed6723b32d20","observation_id":"1d77aa0a-48a0-4b1b-8ecd-9425cf65cf04","resolution":{"observed_at":"2026-08-06T12:47:35.368128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:33.699592Z","title":"Face x-ray for more general face forgery detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.699592Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:7c0525fc2b5fceaa650954b79c10f7956499dabb8c499498ee11588437468853","observation_id":"a0408ff4-6f57-4b90-b633-aefe84a6b1ab","resolution":{"observed_at":"2026-08-06T12:47:33.699592Z","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":"2026-08-06T12:47:35.303789Z","title":"Generalizing face forgery detection with high-frequency features,","venue":null,"work_id":"0ac86e72-6ffb-4023-b61c-31a1e8b9473d","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.707028Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:88c6af7ed709925542317910232c9a4ec51e1c92ab64a941519b2120f8e4e3e3","observation_id":"09c8a3f7-4ecb-442a-bf7f-042f4261c8ad","resolution":{"observed_at":"2026-08-06T12:47:35.314601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.276634Z","title":"Representative forgery mining for fake face detection,","venue":null,"work_id":"d28dd604-a4c4-41f0-bc82-b1f97ce010b7","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.713017Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:61f6e948a2da90def6b7db585ee3c58fa6743b2e89bbeb046a2ed1df90302f54","observation_id":"e0c6915a-8322-4a29-a2c3-c697e5582f59","resolution":{"observed_at":"2026-08-06T12:47:35.282846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.253069Z","title":"Implicit identity leakage: The stumbling block to improving deepfake detection generalization,","venue":null,"work_id":"d3195043-b565-4e1d-8ca8-0670979b3440","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.721838Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:08d9b10097eb909b05d92c3a7ad3e2f649d95f367d637d42adb16dc0ad9cb2bf","observation_id":"9879ed7c-1254-4514-a4f9-d2277e7e1e4c","resolution":{"observed_at":"2026-08-06T12:47:35.261044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.230504Z","title":"Detecting deepfakes with self-blended images,","venue":null,"work_id":"aea042c0-b6e7-4d83-9c00-2131908b56b7","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.729148Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:5df6dc8732143a1c9fc8f03b60e373eaf542dcb057f49f39b063a8b2edaaca5a","observation_id":"d2b0f576-9d4b-4af1-84dd-c706aca0a1dd","resolution":{"observed_at":"2026-08-06T12:47:35.235656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.193422Z","title":"Freqblender: Enhancing deepfake detection by blending frequency knowledge,","venue":null,"work_id":"784c6577-f7a5-4126-b0dc-8787447b8be6","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.734981Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:88c043f8c67568a622f2d8be9a1ab498ab89c92e1d54eac1bc3aed23642ef776","observation_id":"5e9e4478-c10d-4d22-b1f8-c1bbc4c061ff","resolution":{"observed_at":"2026-08-06T12:47:35.202640Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.172187Z","title":"Learning self- consistency for deepfake detection,","venue":null,"work_id":"8f9ad10d-59db-4d72-811a-f251e62f5abc","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.741432Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:f69989c3b9fdba0b2df646694976a68b7d2cba2e80bb1c164956e611ae4f4a10","observation_id":"589c132d-f349-4f47-a083-b31cec07723b","resolution":{"observed_at":"2026-08-06T12:47:35.177638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.147494Z","title":"Text-guided human image manipulation via image-text shared space,","venue":null,"work_id":"d535a6bf-dc0d-4e03-8b6e-9dadc538727f","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.750595Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:ca459eb14a9d8fa95ce5f232bb02cf0fbcfaa3f1ca9d418ea55529b4fd1a0934","observation_id":"cc3f1bca-069a-4349-b9de-39cb09925f04","resolution":{"observed_at":"2026-08-06T12:47:35.158105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.126396Z","title":"Deepfake detection based on discrepancies between faces and their context,","venue":null,"work_id":"58d0d6ce-d9a4-4682-959f-36e9e13d235d","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.756078Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:350cef7d9672c2508c92d5a06f3eeadbaac72c7cb58cb9bc3d7446398955abf6","observation_id":"9da2af78-c3e5-44c1-90cf-689cd46b74df","resolution":{"observed_at":"2026-08-06T12:47:35.132890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.101337Z","title":"Auto-encoding variational bayes,","venue":null,"work_id":"9b8ed517-bcae-425c-818f-fb832c6c6603","year":2014},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.761584Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:3670055c2afd03822ae64faab55506d39620f97547efdabb6dbcda5bda41680f","observation_id":"026aec7d-f079-4427-82a7-78141c0e1832","resolution":{"observed_at":"2026-08-06T12:47:35.107188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:35.072325Z","title":"Generative adversarial nets,","venue":null,"work_id":"440b851d-e3d3-4913-93ec-7f2f558ab5a1","year":2014},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.769645Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:e671147fe9a46b507055e5799e0f026f4ca386f12b062b3e7464bb920e5a5140","observation_id":"2a5f6720-fa2c-469c-9f01-359cde55fc05","resolution":{"observed_at":"2026-08-06T12:47:35.079739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:33.778118Z","title":"Face2face: Real-time face capture and reenactment of RGB videos,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.778118Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:6a5ca759052a2a79b29740ab84b1a2be54c1c1e3d8c8b88f27a5b4fe2af85892","observation_id":"d3ee33eb-3f7f-4150-849a-4d97367af0bc","resolution":{"observed_at":"2026-08-06T12:47:33.778118Z","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":"2026-08-06T12:47:33.786672Z","title":"A style-based generator architecture for generative adversarial networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.786672Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:1752e09cdf7cb5a0a2a222dd219a52bd548d79bbdac3dc633df54e20b901fab0","observation_id":"d351cda1-d367-4f71-b83f-9154c5b546af","resolution":{"observed_at":"2026-08-06T12:47:33.786672Z","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":"2026-08-06T12:47:34.988016Z","title":"Towards open-set identity preserving face synthesis,","venue":null,"work_id":"8910ce88-b0f8-4265-a5b6-e1c1265d39a9","year":2018},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.792318Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:d8c4b4a1b8e376c5dec412bacde4e4bbe8c760b27b09a00fd93477881faf9fc2","observation_id":"876b2cbd-98d5-4eda-931a-026837956ada","resolution":{"observed_at":"2026-08-06T12:47:34.994379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.967417Z","title":"Exchanging faces in images,","venue":null,"work_id":"c6d03b89-e58e-4e78-91aa-32564c24443a","year":2004},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.798268Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:0553f8624c342cab983bc5b3863a197275a163f5f20054a732ab67845defc51c","observation_id":"094d0dd3-9926-474f-9ea9-63bf766dc4d3","resolution":{"observed_at":"2026-08-06T12:47:34.974578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.05564","last_updated":"2023-03-23T11:50:36Z","snapshot_observed_at":"2026-08-01T22:04:45.629414Z","submitted_at":"2022-06-11T16:57:23Z","title":"gDDIM: Generalized denoising diffusion implicit models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.05564","snapshot_observed_at":"2026-08-06T12:47:33.803940Z","title":"gddim: Generalized denoising diffusion implicit models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.803940Z"},"links":{"cited_paper":"/paper/2206.05564","citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:edaf442d10b03b33becc38a2f42a44c5fd920736b91a95b64890bd7988cd9131","observation_id":"47e67046-dc74-4dd1-913b-bc9d652e69fc","resolution":{"observed_at":"2026-08-06T12:47:33.803940Z","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":"2026-08-06T12:47:34.950613Z","title":"Improved denoising diffusion proba- bilistic models,","venue":null,"work_id":"5b693191-796f-4641-a0bc-06762fae0ab2","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.810988Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:2b249bc54b4e0e22ead65d36f8f0ec9fc1c328062fc8178cb029a8de5a5b8594","observation_id":"3d901d40-9c4c-4b95-8d74-9e11871982d5","resolution":{"observed_at":"2026-08-06T12:47:34.955259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.928816Z","title":"BDDM: bilateral denoising diffusion models for fast and high-quality speech synthesis,","venue":null,"work_id":"de3c2d6d-9028-4f20-b2c3-b5408475351b","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.816258Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:10990003da5cc274dbd875b9c6f5b8df481f02e6619409897ff3c09520925454","observation_id":"07c18022-e586-4168-ac64-8d65e4fbdc38","resolution":{"observed_at":"2026-08-06T12:47:34.938639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.904486Z","title":"Denoising diffusion implicit models,","venue":null,"work_id":"b12b97c2-bd17-401d-9153-40fbee3adb46","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.821088Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:d0dceb0ef01213c6367b26613a4f1ccd9516781716257029bd52b01cc2e25128","observation_id":"3ca187eb-e5a8-40b1-9a1a-709d723f698c","resolution":{"observed_at":"2026-08-06T12:47:34.910320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.886964Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":"cfdd99a5-e10b-4bbb-a57b-a0f775e5a2c7","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.826486Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:f92c01f7f4f8d0a0bac5132d752733d83cdac0a1d999cf0c37c619a7ae3c74c9","observation_id":"6e3cb0a3-845e-477a-b954-80825c302c65","resolution":{"observed_at":"2026-08-06T12:47:34.892333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.865330Z","title":"Diffface: Diffusion-based face swapping with facial guidance,","venue":null,"work_id":"8d215bf7-7412-44bc-8ddb-1f55845f7929","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.832619Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:93a502fc1041c193a551ccc0aa43c1e725168281b13fa1cacd8b4a30bb5a6760","observation_id":"179058b3-df9e-4b7e-97f0-13554a9b62be","resolution":{"observed_at":"2026-08-06T12:47:34.871169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.831039Z","title":"Transcending forgery specificity with latent space augmentation for generalizable deepfake detection,","venue":null,"work_id":"e6c04d37-fbb6-497b-a3fe-438f2a0ff6f9","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.840413Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:a98ca55fb9c777caddc15a5ca16ac0be9276477b0c68a140de253332989b8595","observation_id":"396a11d5-8e16-4b9c-916b-62994aad645f","resolution":{"observed_at":"2026-08-06T12:47:34.843999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.807822Z","title":"Improving generalization of deepfake detectors by imposing gradient regularization,","venue":null,"work_id":"6df6955e-46de-4e4d-8649-f62a874354fd","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.847423Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:4692ff3378f05c100382fe0def5e5ea4530446d7e1626805b54338d3846bf3c1","observation_id":"5d6a1ac7-9415-456e-9356-40b78b0283b4","resolution":{"observed_at":"2026-08-06T12:47:34.812827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.04384","last_updated":"2025-05-07T13:05:32Z","snapshot_observed_at":"2026-08-01T18:50:38.304694Z","submitted_at":"2025-05-07T13:05:32Z","title":"DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attribution","version":1},"cited_work":{"arxiv_id":"2505.04384","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.04384","snapshot_observed_at":"2026-08-06T12:47:34.078474Z","title":"DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attribution","venue":"cs.CV","work_id":"77beec16-e731-447e-8eda-f764926e7892","year":2025},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.856259Z"},"links":{"cited_paper":"/paper/2505.04384","citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:bef5e8da2cae167cfa0bd410a7b729724acdb7eb5f4c5c6cf1006cde4aa42a8e","observation_id":"f2b46da0-5353-4c83-bfbd-27cfb12a771c","resolution":{"observed_at":"2026-08-06T12:47:34.086641Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.789414Z","title":"Exploring frequency adversarial attacks for face forgery detection,","venue":null,"work_id":"932e8c30-feed-4fe6-9e81-0ce73eaf4233","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.862750Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:c41a39a8e58cf274fd80f788d2a0be034932208a93c76006548a6e98fd9c4ee4","observation_id":"d3c49632-1ffb-4685-bad7-22bf32e6153c","resolution":{"observed_at":"2026-08-06T12:47:34.795005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.773012Z","title":"Sstnet: Detecting manipulated faces through spatial, steganalysis and temporal features,","venue":null,"work_id":"685860d0-fe05-42b2-a144-c331cba78503","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.869272Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:b8b55990f78546de6226f1e5ec8c21c3424b791aaba9f5c704739482a4eff31a","observation_id":"bb53a9b7-7d3d-4d6c-af55-57c3690fd08f","resolution":{"observed_at":"2026-08-06T12:47:34.778065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.726298Z","title":"Multi-factor adaptive vision selection for egocentric video question answering,","venue":null,"work_id":"eb54ba86-01d8-4a9d-862f-a6ea478d351b","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.874789Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:a90e2b90c6d973773e9c799496ba0207664b73f3814bae2712be5693fa9466b4","observation_id":"cea4ce7b-9dc1-4d89-ab0a-dccaa5888035","resolution":{"observed_at":"2026-08-06T12:47:34.742577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.679963Z","title":"Efficientnet: Rethinking model scaling for convolutional neural networks,","venue":null,"work_id":"2bf21648-9ecf-46ba-a3f5-75f6498320a7","year":2019},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.879688Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:2d20ee04e04b5e991bd9c067c99420deec0fc13891017889297dda0d5d680d3f","observation_id":"5e364a2d-70f6-48d9-b3a8-7a170545581d","resolution":{"observed_at":"2026-08-06T12:47:34.695334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.636953Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":"df3a5686-dabf-4886-954b-ef7a9f01587b","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.885155Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:b8a312ae755db573c1d6597093feea4f82cd3458ddeea1c62fe39b99a8c69b23","observation_id":"be70ed2b-3618-43b8-b866-72c849e4ae90","resolution":{"observed_at":"2026-08-06T12:47:34.651928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.615735Z","title":"V oice-face homogeneity tells deepfake,","venue":null,"work_id":"41183ce3-13e6-4376-ad47-23c8f3ada391","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.890075Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:be62de1f6036dd86d0bb2bd098ada673cc71b4ac4560a6169d0a266d94088300","observation_id":"c668f52a-a34e-44ac-8837-17aee89ab28b","resolution":{"observed_at":"2026-08-06T12:47:34.622391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.581677Z","title":"Leveraging real talking faces via self-supervision for robust forgery detection,","venue":null,"work_id":"72959f52-cbcd-460f-98e4-869878dce788","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.895074Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:4d14a82d0ba2496ffeecca4397b792cacee357323b44e59b5cc87338eda3e830","observation_id":"95a536e7-dc4c-4771-95a8-eb01843b194f","resolution":{"observed_at":"2026-08-06T12:47:34.591682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.556549Z","title":"Emotions don’t lie: An audio-visual deepfake detection method using affective cues,","venue":null,"work_id":"808e400a-af0a-4463-b8bf-aa506a5b5d07","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.900082Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:d9e65e1c0c26f3f50343cab750102eb9f79942f5550f6b11965a29589891717c","observation_id":"4ebc9df6-764a-4486-815a-69ff29b35b5e","resolution":{"observed_at":"2026-08-06T12:47:34.564144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.536211Z","title":"Dual contrastive learning for general face forgery detection,","venue":null,"work_id":"3946fe6c-7000-4f13-9ebd-9ea88652515b","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.904825Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:a694ddb139b4b6cac98da124642c7e5e9741d566a496becb74fd2f1acb4120af","observation_id":"f2d12443-127a-4dae-9aa1-086a3b1adaf2","resolution":{"observed_at":"2026-08-06T12:47:34.541660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.516716Z","title":"Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection,","venue":null,"work_id":"a586ee3e-23bf-4b43-8beb-60d33842c705","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.909439Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:fba685b6775b6f3a860844c7b17655d64c8c4acd8b79369923b3fe61499ec155","observation_id":"d1b88a7d-bb19-4690-b029-d044d43549f2","resolution":{"observed_at":"2026-08-06T12:47:34.522307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.495744Z","title":"UCF: uncovering common features for generalizable deepfake detection,","venue":null,"work_id":"7d27eef8-c944-427e-9b0b-2a80ef9c726a","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.914598Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:092629562a55ef9dca933c1064d5f932adb9bdc13583cf46ad892b4f5bb3d87b","observation_id":"0d7a44f9-722b-44ea-9514-66df371b98cb","resolution":{"observed_at":"2026-08-06T12:47:34.502452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.467815Z","title":"Towards more general video-based deepfake detection through facial feature guided adaptation for foundation model,","venue":null,"work_id":"fd4ec05c-0749-426c-aec3-2b44fab8d30e","year":2025},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.920438Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:3342115bd6d832612f24aa7d60f7a7daa744ba82589a5cb7e15ae4af5bddb752","observation_id":"7adcf623-45df-44d7-bd0d-73b8fd068c64","resolution":{"observed_at":"2026-08-06T12:47:34.474826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.442117Z","title":"Conflict-averse gradient descent for multi-task learning,","venue":null,"work_id":"05503daa-91b5-4b53-ab3a-429944c4d4a5","year":2021},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.925755Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:297c7d55882a1e847b412e56b1ca9f5bcbb288823b9fa143decfd53b585a898f","observation_id":"99633e12-f339-4bb3-a198-523349475d6c","resolution":{"observed_at":"2026-08-06T12:47:34.450582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.421943Z","title":"Gradient surgery for multi-task learning,","venue":null,"work_id":"9a1aa725-aa2b-41f0-ae0b-57c9fd33783c","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.932202Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:135fa048488c315452c10f62b0aac5b1ebe46851e8d67584213e7db2da33a31b","observation_id":"9d33cd8a-4596-4103-8248-ad8a9e48dde0","resolution":{"observed_at":"2026-08-06T12:47:34.428212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.402381Z","title":"Gradient alignment for cross-domain face anti-spoofing,","venue":null,"work_id":"be66d930-d9d9-4915-a60d-b0e7adb04e38","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.937696Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:c127b6d53621aecb8a9792f83737dd59e0c70089a9f80ddf58f494dceed175a2","observation_id":"6d95cc4d-ac71-43ff-8e60-0362ab36ad39","resolution":{"observed_at":"2026-08-06T12:47:34.408177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.381456Z","title":"Sharpness-aware gradient matching for domain generalization,","venue":null,"work_id":"92b25b45-f559-4446-aab9-54d97bdccde6","year":2023},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.942744Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:7fcead9e22fb324c43e2fb8aa5c3248f32f428859ab885bbaf1a44974c1a4057","observation_id":"480496aa-e6d5-4de3-a3b1-424e76f5c293","resolution":{"observed_at":"2026-08-06T12:47:34.387904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.361602Z","title":"Nasvit: Neural architecture search for efficient vision transformers with gradient conflict-aware supernet training,","venue":null,"work_id":"db9a679c-c8ab-463d-95a4-3aef4039d7c5","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.948508Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:18830cffc3e195c241fdf9f20dedb21a3a99b93f503c9edf6ba8ffc95477c4ef","observation_id":"ebf60d28-0eb9-45ba-9f5d-84b78ec68e34","resolution":{"observed_at":"2026-08-06T12:47:34.366877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.340353Z","title":"Celeb-df: A large-scale challenging dataset for deepfake forensics,","venue":null,"work_id":"3e50eff9-3570-4790-bb16-1f430be9b6a3","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.954307Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:20878d16d0da7f115b5557a8a2e0cbb293b11cd4f26a89da2f6ac09b7e205379","observation_id":"0ed05310-dff4-48d3-9933-df5e04c32f64","resolution":{"observed_at":"2026-08-06T12:47:34.346492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.321585Z","title":"The deepfake detection challenge dataset,","venue":null,"work_id":"9c0c5f2a-c273-47fd-9c06-0b1b09a3219d","year":2020},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.959953Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:0bc7653e08e83a2ab5d298c6d912294407a32201393a2d5f26ee7a20b44ff8c4","observation_id":"c668e9b2-5793-4480-8148-810e4321912f","resolution":{"observed_at":"2026-08-06T12:47:34.327505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.303012Z","title":"In ictu oculi: Exposing ai generated fake face videos by detecting eye blinking,","venue":null,"work_id":"50400890-075e-4ff8-a089-f9a120f26d0f","year":2018},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.965482Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:8ba9fc0648719dab0d79720c8846fd101c12c8e6ac9f4f3d5d0b7e0006e0bbf1","observation_id":"afb509a1-f4f4-41d1-96a1-49ad053cd899","resolution":{"observed_at":"2026-08-06T12:47:34.308867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.280150Z","title":"CORE: consistent representation learning for face forgery detection,","venue":null,"work_id":"1c0b08bc-043a-49de-94f1-95ff9c187746","year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.972387Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:db152f6a00c7d9f7f4a68ddc107748ad4250e399105947e97f64ede1866ea777","observation_id":"f8ab4a6f-9adf-41e3-876a-b80799cc56dc","resolution":{"observed_at":"2026-08-06T12:47:34.287559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:33.979129Z","title":"End-to- end reconstruction-classification learning for face forgery detection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.979129Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:20f0ada53d4178198779115c999d060e10c3a5000b2bab52c0fdd178a1c1979c","observation_id":"92c47846-41ae-4e32-9e4b-cac64df1713d","resolution":{"observed_at":"2026-08-06T12:47:33.979129Z","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":"2026-08-06T12:47:34.241160Z","title":"Learning to discover forgery cues for face forgery detection,","venue":null,"work_id":"63eeaefb-5ca8-404a-99a9-0c2c149a29bb","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.983954Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:6d2e477ab45701d67dfcd5d99450cb06dbd689c09fe1a4defdd67a7953364150","observation_id":"d0fe9d2e-7237-48a7-837d-957ff69b10d3","resolution":{"observed_at":"2026-08-06T12:47:34.246841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.222125Z","title":"Fully unsupervised deepfake video detection via enhanced contrastive learning,","venue":null,"work_id":"4d1aeef5-fc43-4823-ad9e-f4b96df8eb1d","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:33.995992Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:3bbb6a8690dc750a5fd034bc8f5312c38d0540a678f008433e5162dbb843a7c9","observation_id":"f8405602-c046-4548-a07c-5ec4dd9039ec","resolution":{"observed_at":"2026-08-06T12:47:34.228003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.202441Z","title":"Exploiting style latent flows for generalizing deepfake video detection,","venue":null,"work_id":"cf0f1163-d5e4-48e1-9407-f451971aa494","year":2024},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:34.001913Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:1e1f197ecd28845fa0832c12167996d37d1392ac5834289050f075d2c929d06e","observation_id":"da6e5736-4c87-4d79-a813-f3b46febc1e6","resolution":{"observed_at":"2026-08-06T12:47:34.208529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.183379Z","title":"Orthogonal subspace decomposition for generalizable ai-generated image detection,","venue":null,"work_id":"efb50211-47bf-4192-9460-cc026ab06808","year":2025},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:34.010153Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:497701f524c0c341e8774a6aaa939db8da70e6f01f2602d8cea05540a163fd08","observation_id":"51e4cdfc-cfa2-4698-a84a-671ae994a648","resolution":{"observed_at":"2026-08-06T12:47:34.189342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T12:47:34.166962Z","title":"Towards general visual-linguistic face forgery detection,","venue":null,"work_id":"ba791cca-7287-4b82-a10d-796460939686","year":2025},"citing_paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T12:47:34.016786Z"},"links":{"citing_paper":"/paper/2507.21530"},"observation_digest":"sha256:68ac578553befd0e3664c8d9ed5ecfcb7f9bf2cefe2e993e1d2ce0ea6a89a087","observation_id":"6100ca02-0d21-4c14-8050-bbf503713132","resolution":{"observed_at":"2026-08-06T12:47:34.171680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.21530","last_updated":"2025-07-29T06:48:22Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T12:47:32.011750Z","submitted_at":"2025-07-29T06:48:22Z","title":"Suppressing Gradient Conflict for Generalizable Deepfake Detection"},"reference_resolution":{"displayed":71,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":2,"verified_fuzzy":64},"total_outbound_references":71},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2507.21530."}