{"as_of":"2026-08-09T23:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:74728c44ea3428585b7d51ff4b2dee34291741d1ca6fbfbc8cdddd4df5353ab8","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T19:36:37.333042Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T19:36:37.333042Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-02T21:37:25.490420Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"cited_work":{"arxiv_id":"2606.08038","doi":null,"metadata_source":"pith","pith_arxiv_id":"2606.08038","snapshot_observed_at":"2026-07-02T21:37:25.490420Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","venue":"cs.SD","work_id":"3e844803-db2a-4735-81cf-663bb3fc8b5d","year":2026},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2606.08038","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:4c46be3187b2cf2c0b83e2e5a1142d5f51508e4ceae335e0f2370d6b0f344d2c","observation_id":"d9848da5-d60b-49f6-9c2e-e511306fa3f5","resolution":{"observed_at":"2026-07-02T21:37:25.491658Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2606.08038/citation-record","integrity":"/paper/2606.08038/integrity","json":"/paper/2606.08038/citation-record.json","paper":"/paper/2606.08038"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"cited_work":{"arxiv_id":"2606.08038","doi":null,"metadata_source":"pith","pith_arxiv_id":"2606.08038","snapshot_observed_at":"2026-07-02T21:37:25.490420Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","venue":"cs.SD","work_id":"3e844803-db2a-4735-81cf-663bb3fc8b5d","year":2026},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2606.08038","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:4c46be3187b2cf2c0b83e2e5a1142d5f51508e4ceae335e0f2370d6b0f344d2c","observation_id":"d9848da5-d60b-49f6-9c2e-e511306fa3f5","resolution":{"observed_at":"2026-07-02T21:37:25.491658Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"Fake Speech Detection Fake speech detection aims to distinguish generated speech from real speech","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:065442e9d513b9646a1e0bfbea68c8fb8b7c4db132f7c0760fb10295bb3f113a","observation_id":"d1a91ab0-ff74-4652-a28a-ac66f78ebc30","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:931b0a25743813a287a28792d756ca9d1c6380d953b8cb3c6c301a59ef9971e7","observation_id":"c6c464dc-3154-47e6-b1de-72dbfa67edf7","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"We conduct a systematic analysis of the results and derive the following two key findings","venue":null,"work_id":null,"year":1982},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:52c02e1134c24240b047b5f672ed6a08d2571f83833ce91b88cc9c86a69e3503","observation_id":"1a153f7a-3025-4a6b-b129-a16ae06852d6","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:e9767879e42b79ba8c2da96fae583c7a029e3a39587c00afc5a550f6b994b3ed","observation_id":"fe1544eb-005e-46e1-9295-edabc3c12533","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Motivated by this observation, we conduct two exploratory experiments to examine how training data scale and diversity affect model performance","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:fe1e18ff7cee36860a0be576047da880906d3151f3d6f772400c8728d70abaf0","observation_id":"543816c6-effa-44e0-83c4-a9e8b4dc6ce8","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:a27e1ce2107bd648746fd926096734e6f2b17d42a02fc5ffb831840f76c2297e","observation_id":"96422ba3-6fb9-4709-8432-96255a1abc79","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"The research design, experiments, analysis, and conclusions were conducted and verified entirely by the authors","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:42df0e8f7b5fd54b2378ce646b4bd7fedb7c97792f192dc57c093eef05d422bb","observation_id":"8d887d56-dd22-47ed-92a3-ce6771408881","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Towards con- trollable speech synthesis in the era of large language models: A systematic survey,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:d498df5f4189dcf4a5d76d656f26f8747f3bfa52eb4bc2d330fdc0f3f735c77a","observation_id":"6ae4468a-759f-48e0-86da-c98c41a0c5bf","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"A survey on speech deep- fake detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:b4c31470abbba4bbef85e03f99488a29570a1e5981e6e98b610009e39c0e36f4","observation_id":"4982f482-bc55-47ae-960a-525de239ee68","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Asvspoof 2015: the first automatic speaker verification spoofing and countermeasures challenge,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:bcbcf9e0a40fdc223174538c1908c69eb70d565ea9f2cc1f0652883b933aad76","observation_id":"e632b531-85a7-4db0-8a16-ad190c63b9cf","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Asvspoof 2019: A large-scale public database of synthe- sized, converted and replayed speech,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:912dbb6bf8fb7a46e07a9089d280c5e75917d988d86874a0e2b28eae1b8bbdca","observation_id":"93bc3db6-c8a5-4573-8dd0-12b95921afd3","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:a7b7cf151cf23a26adacf0e33a12c8431bf42ace593bf4a5f13f02a153b00df5","observation_id":"439ec705-6e99-4f16-ab23-0bcf247fd345","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:6b6ebd0a0be5aa42f13f78dd0a48cdd6aef303cf4caf681d9f4bff462ed3b827","observation_id":"aaabb4a2-31ba-41e4-8bb9-0326592bc9f9","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Speechfake: A large-scale multilingual speech deepfake dataset incorporating cutting-edge generation methods,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:b3efd9660d12995f8ca8bbdd2d2aaa132df40097855f9da120f23267bd1a665f","observation_id":"0aefb5a3-69e1-4d22-b24a-2c3b8e4cd61f","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2506.21090","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T21:37:25.495539Z","title":"Post-training for deepfake speech de- tection.arXiv preprint arXiv:2506.21090","venue":null,"work_id":"f6d62c6a-5d65-47ef-8b15-44fa1a619d08","year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:fc5b055694ca139586ad893828b4117820a07c20a9c2a1bb4753d3da44f8c22f","observation_id":"26e5b498-15f4-4a10-a6d9-1c297443997d","resolution":{"observed_at":"2026-07-02T21:37:25.497117Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"Spoofceleb: Speech deepfake detection and sasv in the wild,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:f250990947bfd9b7db8c1949ed483d9174989f5be83884ee2a2c2782479a7d43","observation_id":"286317ee-95d6-4b37-93b0-5f3b5c9ea1d8","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2512.18210","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T21:37:25.492865Z","title":"A data-centric ap- proach to generalizable speech deepfake detection","venue":null,"work_id":"3b21b8d7-2ff8-4191-b82b-b6ee90ca7cbc","year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:e021cc71c8c71fe26da02527d44a88bf404f987a3073bd03126b6dc1e748736a","observation_id":"f877d2d0-2914-4d7a-86a7-f27a5860a26b","resolution":{"observed_at":"2026-07-02T21:37:25.494373Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"Deep residual neu- ral networks for audio spoofing detection,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:414b21b2cc5dcb2b7ea46105add02f9cc05cadb8db1cfeac9487e08d9281ede4","observation_id":"c95931e5-4d2c-4dec-ae55-848a7d39c0ac","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Deepfake audio detection via mfcc fea- tures using machine learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:a7cd571c2c4ad23f014e6d9ce48a2f8f5a7aa52c0bdc58452938c46c77c7a245","observation_id":"39db76ef-a1d8-44a7-b1a2-95e235e84bee","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Is synthetic voice detection research going into the right direction?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:2f7e004b4b7f9ff6303c7851a2a1c553a72935fae6500744a4503ee570d736c8","observation_id":"ced03eba-8885-40b7-8392-a43b5537b760","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Audio deepfake detection based on a combination of f0 information and real plus imaginary spectrogram features,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:5721e3a96a733dc78ad9cd446b032adcbf19241b4a00ced8b0a8d503a901bf39","observation_id":"0ecef8f1-854e-4d06-9551-99896b7af20f","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Learning from yourself: A self-distillation method for fake speech detection,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:cd143d60b890db4220e39fdc3c496c32cd712748a1077dd0770c8df618638a0c","observation_id":"806ccf4f-a2b8-402f-99a0-cb8338ad4663","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Deepfake speech detection through emotion recognition: A semantic approach,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:bd55844704db00fe667db16c05007783993857068d5728edd54799a926792ceb","observation_id":"fad92304-ec5d-4536-848e-3d3f333bec24","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Bts-e: Au- dio deepfake detection using breathing-talking-silence encoder,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:dccfcf83dd7faf6b25b049dbf755a0d385f5c01df12b37d33142f04192ea7c9a","observation_id":"4794fc30-cd18-4f01-858d-f67eae6c4e27","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"End-to-end anti-spoofing with rawnet2,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:0659fb909434b8465704171bcab4929065650ae577d41bc406c50ccdded71977","observation_id":"c002e96c-49f9-49ea-a369-b735dbe76d1d","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"End-to-end spectro-temporal graph attention networks for speaker verification anti-spoofing and speech deepfake detec- tion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:d4051a586429fed22b437d1933dc3e93d22eea8d2c61dbccb9d2c9af57ec586b","observation_id":"fd681f5f-fffc-46c4-ad78-6a993e4eb85a","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Aasist: Audio anti-spoofing using in- tegrated spectro-temporal graph attention networks,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:c0c82ebec21d817b2d5b6e3cb2e7490b45b881e70026e005c0f052a7ed55ac8c","observation_id":"591ee6f9-9ad3-4ebe-b642-580aa1f502b6","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Automatic speaker verification spoofing and deep- fake detection using wav2vec 2.0 and data augmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:9b5fe358613a84ded3f1ac79e09491006061983005369ba707e261ed4ca57e3e","observation_id":"7c168b74-cf08-440d-b703-2f3cee5aed73","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Multi-level ssl feature gating for audio deepfake detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:68c25f1510c50cb6715e9984357b42ba6dab551f1b745d7830f6d9a1d4107f65","observation_id":"649a6bf1-1433-44b9-ad3e-121ab8024ba8","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Fmfcc-a: A challeng- ing mandarin dataset for synthetic speech detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:9357ebfd44113ba5b57f80ab7b7cd2152dfcac38cef60143cc3774d55faac1ae","observation_id":"b348dc92-5d51-4ce0-a8e1-cf9d8299cf63","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Add 2022: the first audio deep synthe- sis detection challenge,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:85360df09786d6388dd14146763e2b49e543b5297c87af27d6fd2192411c62d5","observation_id":"34f54320-c295-4098-8869-c7940632d860","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13774","last_updated":"2023-05-23T07:42:52Z","snapshot_observed_at":"2026-07-06T15:31:13.189124Z","submitted_at":"2023-05-23T07:42:52Z","title":"ADD 2023: the Second Audio Deepfake Detection Challenge","version":1},"cited_work":{"arxiv_id":"2305.13774","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.13774","snapshot_observed_at":"2026-07-04T02:19:22.853731Z","title":"ADD 2023: the second audio Deepfake detection challenge","venue":null,"work_id":"808718ce-d91e-44e4-9c14-ac5308ad8428","year":2023},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2305.13774","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:0eb11462169bbfc3010d88f775ac98f055e93729f6c61f09c4da1a4eac900d99","observation_id":"bcce51a8-6569-4025-bb95-d37910b1d1fb","resolution":{"observed_at":"2026-07-02T21:37:25.483437Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"Diffssd: A diffusion-based dataset for speech forensics,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:17ef3b643bd41195c44c62304645b6cb420298dfb01a20ea291d29f84b59c1d3","observation_id":"43e98c0b-dbdd-422a-8e21-ab5786b22ff8","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Diffuse or confuse: A diffu- sion deepfake speech dataset,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:61611c0e219ab417c4966b782b189e83040f7f3923bd909bfd0bc0da77a3efad","observation_id":"20aa02d2-bf09-41f2-b946-485256d1fb98","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Codecfake: Enhancing anti-spoofing models against deepfake audios from codec-based speech synthesis systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:7dc64e4a3d6e0a5599233d70fcfb28e586c1559ff9a07606369b0a4b303e5611","observation_id":"2d8e481a-df36-451c-bcea-e29541430010","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"The codecfake dataset and countermeasures for the universally detection of deepfake audio,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:3b57caa4cc77135eb3192ba76b8f1b028ec2b7a406392b3c50f129e824c4b14a","observation_id":"d4001481-6de8-4040-bc75-523d7e8a6956","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Collecting, curating, and annotating good qual- ity speech deepfake dataset for famous figures: Process and chal- lenges,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:b15bacd793a5ecc34d88b841589b253e37d1eb32ea4fc1b1d8f043fb46c02970","observation_id":"eaf42cc6-7dae-4e44-afbd-25ed18365f92","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.17737","last_updated":"2026-05-18T01:36:46Z","snapshot_observed_at":"2026-08-02T07:35:19.943282Z","submitted_at":"2026-05-18T01:36:46Z","title":"Profiling the Voice: Speaker-Specific Phoneme Fingerprinting for Speech Deepfake Detection","version":1},"cited_work":{"arxiv_id":"2605.17737","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.17737","snapshot_observed_at":"2026-07-02T21:37:25.484528Z","title":"Profiling the Voice: Speaker-Specific Phoneme Fingerprinting for Speech Deepfake Detection","venue":"cs.SD","work_id":"4d6651c7-bd54-4550-b07b-541a299135b1","year":2026},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2605.17737","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:86ee2344aa708b6d785632b5234cb3926137b01185239dd7b5731103ffe19ee6","observation_id":"b7a8fd68-cbf8-40d8-b1c4-d2bf8e18eff9","resolution":{"observed_at":"2026-07-02T21:37:25.486076Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10559","last_updated":"2025-08-14T11:56:30Z","snapshot_observed_at":"2026-08-05T20:23:03.424991Z","submitted_at":"2025-08-14T11:56:30Z","title":"Fake Speech Wild: Detecting Deepfake Speech on Social Media Platform","version":1},"cited_work":{"arxiv_id":"2508.10559","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.10559","snapshot_observed_at":"2026-07-02T21:37:25.487232Z","title":"Fake speech wild: Detecting deepfake speech on social media platform,","venue":null,"work_id":"1d553dfe-7162-4076-9212-ac36214b3111","year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2508.10559","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:c0bbe2b141e4bd4f9d4ddabc80b5fdc43203dd01b4bcc3e41a76b6e392c0a8ba","observation_id":"0ef1658b-9b3d-45ba-a53c-d11e768ef690","resolution":{"observed_at":"2026-07-02T21:37:25.488616Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"Does audio deepfake detection generalize?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:10c792de6850f2851f02b83ad5bf9176b87f4115bdb59d9cba361b5a83541088","observation_id":"75aea1f0-66ce-42d2-97ed-a93799661c7a","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.23742","last_updated":"2026-04-26T14:42:50Z","snapshot_observed_at":"2026-07-06T23:09:52.860780Z","submitted_at":"2026-04-26T14:42:50Z","title":"RTCFake: Speech Deepfake Detection in Real-Time Communication","version":1},"cited_work":{"arxiv_id":"2604.23742","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.23742","snapshot_observed_at":"2026-07-02T21:37:25.479838Z","title":"RTCFake: Speech Deepfake Detection in Real-Time Communication","venue":"cs.SD","work_id":"966eebcb-6e8b-4645-bb8e-d84825374d07","year":2026},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2604.23742","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:e16a454bda2b3b75e82d93d94d3bbd19889ecbe7613bda1427dd5b2a75a8725f","observation_id":"288b955f-2b85-43ea-9816-86170a2faf6c","resolution":{"observed_at":"2026-07-02T21:37:25.480999Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"V oicewukong: Benchmarking deepfake voice detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:ead9b36220e9054cd65be42c4d397d0f8615690a636d73c2dfd439b831dc950a","observation_id":"015d2430-0a5e-471b-9338-7755d1ec72fb","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","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":"2026-06-27T19:36:37.333042Z","title":"Mlaad: The multi- language audio anti-spoofing dataset,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:d4b95691886ef42cfe7423153f5f098a0854c0c2a3411834aa78378c9f0aeec4","observation_id":"076b673f-8e79-4d48-8fbd-df199b2e884c","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.04904","last_updated":"2024-09-20T08:08:53Z","snapshot_observed_at":"2026-08-02T07:29:06.585819Z","submitted_at":"2024-04-07T10:10:15Z","title":"Cross-Domain Audio Deepfake Detection: Dataset and Analysis","version":2},"cited_work":{"arxiv_id":"2404.04904","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.04904","snapshot_observed_at":"2026-07-02T21:37:25.477180Z","title":"Cross- domain audio deepfake detection: Dataset and analysis,","venue":null,"work_id":"ff1520cf-0dae-43dd-a378-5d20626a98f3","year":2024},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"cited_paper":"/paper/2404.04904","citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:855d7e1d0ccdb927b273a3fd3227891e37c08ae757fd270d4f7e165f31c45be8","observation_id":"39f8831e-3922-48e3-a515-16adc0022426","resolution":{"observed_at":"2026-07-02T21:37:25.478644Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-06-27T19:36:37.333042Z","title":"Raw- boost: A raw data boosting and augmentation method applied to automatic speaker verification anti-spoofing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-27T19:36:37.333042Z"},"links":{"citing_paper":"/paper/2606.08038"},"observation_digest":"sha256:b8ff037ee720b753bc63f4d5aeef3d2d90d5f3e4d97700d2294c5beed28f27cd","observation_id":"a48c2bea-f5a6-408c-981a-82c4640f87a3","resolution":{"observed_at":"2026-06-27T19:36:37.333042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.08038","last_updated":"2026-06-06T07:58:02Z","latest_version":1,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-02T19:28:51.723917Z","submitted_at":"2026-06-06T07:58:02Z","title":"Exploring the Scale and Diversity of Speech Anti-spoofing Datasets: Experiments and Analysis"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":38,"verified_exact":8,"verified_fuzzy":0},"total_outbound_references":46},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2606.08038."}