{"as_of":"2026-08-08T03:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cca0bd91015562d07454b9fe3a7460438835cffcc1f9b40ff41df1da315518bb","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T10:41:03.296949Z","state":"measured"},{"denominator":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"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/2509.03829/citation-record","integrity":"/paper/2509.03829/integrity","json":"/paper/2509.03829/citation-record.json","paper":"/paper/2509.03829"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:41:04.574769Z","title":"Diffcss: Diverse and expressive conversational speech synthesis with diffusion models,","venue":null,"work_id":"4e147bc8-1407-42f9-bb40-5a4c955fbacb","year":2025},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:02.968318Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:2eadcf42103e4f2d8492942d4a46d0b8f4196f75edc6db6a07fda26605b76b9c","observation_id":"9325b512-63be-4c84-a60d-c861bf65fd0a","resolution":{"observed_at":"2026-08-05T10:41:04.583176Z","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":"2026-08-05T10:41:04.528850Z","title":"Stable- tts: Stable speaker-adaptive text-to-speech synthesis via prosody prompting,","venue":null,"work_id":"5f8cf15b-322a-4851-bf24-fde85bf47856","year":2025},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:02.989450Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:286f00c0bf12f3f173b4892ee3f96bb357e6a82a439a7aa8fd6763f587919e56","observation_id":"6f1c16f4-65e0-4622-89e9-f013c0e76a2d","resolution":{"observed_at":"2026-08-05T10:41:04.544004Z","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":"2026-08-05T10:41:04.480785Z","title":"Grad-stylespeech: Any-speaker adaptive text-to-speech synthesis with dif- fusion models,","venue":null,"work_id":"d8b69c99-7ea4-4d26-9144-bc56b6cb7376","year":2023},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:02.996926Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:58e2d33df4d1475a9eab9d30bde81034a81069cc1382afa0ef5de59567b41bc7","observation_id":"5d14131c-b90c-4db3-9992-b23f82361d27","resolution":{"observed_at":"2026-08-05T10:41:04.495186Z","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":"2026-08-05T10:41:04.424090Z","title":"Freevc: Towards high- quality text-free one-shot voice conversion,","venue":null,"work_id":"f6a1efa6-53e8-4c68-82e1-7b2005ed97cb","year":2023},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.007408Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:36e09271fa5b8b5d2e97da041b8d3d93b5445c587a36a8490ddd8403ea4bc681","observation_id":"dd468327-e3fe-42f6-910e-fab8c23da67f","resolution":{"observed_at":"2026-08-05T10:41:04.439815Z","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":"2026-08-05T10:41:04.386847Z","title":"Speechsplit2.0: Unsupervised speech disen- tanglement for voice conversion without tuning autoen- coder bottlenecks,","venue":null,"work_id":"1f9a77e4-a066-4f71-bbc5-99ef376a53fc","year":2022},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.022214Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:e5da6a17db175b28bbafafd9a207e1aaf7150341d2ffd1a291d80263d45b6cb5","observation_id":"3b84e054-a639-4d02-b893-2189e57617de","resolution":{"observed_at":"2026-08-05T10:41:04.393120Z","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":"2026-08-05T10:41:04.352328Z","title":"Again-vc: A one-shot voice conversion using activation guidance and adaptive instance normalization,","venue":null,"work_id":"cb374ee7-5b23-4dff-9c6c-d382a05ff4d9","year":2021},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.033304Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:0d6101d895fce35b4ab17ef8a2816ca659f0ece9aa1e53c95886938c877cb23e","observation_id":"048f8bc3-8ce8-4313-87d2-511267a37522","resolution":{"observed_at":"2026-08-05T10:41:04.366622Z","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":"2026-08-05T10:41:04.294827Z","title":"Avqvc: One-shot voice conversion by vector quantiza- tion with applying contrastive learning,","venue":null,"work_id":"929f5013-c6a5-4a62-9fe6-744c3229bddb","year":2022},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.050674Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:e4036d1677b568f451b1d6744c87f031fd68e895d4b92ac3f093e513e4f61929","observation_id":"3e1804e3-5e81-4e84-a479-6f867bb92055","resolution":{"observed_at":"2026-08-05T10:41:04.318328Z","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":"2026-08-05T10:41:04.268178Z","title":"Enhancing expressive voice conversion with discrete pitch-conditioned flow matching model,","venue":null,"work_id":"f7a69f88-ae59-46e6-84de-e1a84e8ec791","year":2025},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.068339Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:bfdeaf6df35369d75d13cfa4180bfb9d1942f8406ae997f8fbfd254df71db965","observation_id":"54d83513-d58e-4140-affc-ea5af4949d64","resolution":{"observed_at":"2026-08-05T10:41:04.275957Z","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":"2026-08-05T10:41:04.218990Z","title":"Hifi-gan: Generative ad- versarial networks for efficient and high fidelity speech synthesis,","venue":null,"work_id":"f8ebb5f5-4f6d-4109-9722-32f8cfd8da16","year":2020},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.078415Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:e19aab42494ee2df73f639aef9214d8588c0660d86e0ce666d6230f1c171a65a","observation_id":"1245e7d6-3528-4e52-93d4-8e8d9498b99e","resolution":{"observed_at":"2026-08-05T10:41:04.245373Z","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":"1609.03499","last_updated":"2016-09-19T18:04:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-09-12T17:29:40Z","title":"WaveNet: A Generative Model for Raw Audio","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.03499","snapshot_observed_at":"2026-08-05T10:41:03.093578Z","title":"Wavenet: A generative model for raw audio,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.093578Z"},"links":{"cited_paper":"/paper/1609.03499","citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:0ee5a30894c4712f001d06f8198023692cf4cba165f3f0dc5b0bbb13d7dbcf80","observation_id":"bd41caa9-3391-42cf-bfb2-53758dab346e","resolution":{"observed_at":"2026-08-05T10:41:03.093578Z","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":"2026-08-05T10:41:04.108991Z","title":"Natural tts synthesis by conditioning wavenet on mel spectro- gram predictions,","venue":null,"work_id":"d8c11642-9450-4339-ae41-39481b2d70b3","year":2018},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.118778Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:6cd4d48e6599339b978a4a593eca26a7a08632ca0b2a3d80902f42e1cfeba98d","observation_id":"b03fa801-ba11-45cf-9efd-82159b707d47","resolution":{"observed_at":"2026-08-05T10:41:04.179626Z","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":"2026-08-05T10:41:04.042337Z","title":"End-to-end anti-spoofing with rawnet2,","venue":null,"work_id":"4efadc40-6d5c-47d8-b5ba-b0607e25d496","year":2021},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.132533Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:4d7aa872872adc860f00ce5523989814af95e5fa19c1855a14f349d9c2fd6150","observation_id":"2fda5db6-1b1c-4351-bb0d-30f7b1ef3ac6","resolution":{"observed_at":"2026-08-05T10:41:04.053161Z","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":"2026-08-05T10:41:04.011226Z","title":"Aasist: Audio anti-spoofing using integrated spectro-temporal graph attention networks,","venue":null,"work_id":"1685b00e-f574-4c7d-bf2d-359cd16c1b88","year":2022},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.149016Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:196ac27905604dde454e6c44718f05f4b46e723eb27f659089a0d2e3b49fd4b8","observation_id":"a26bda3c-2bf8-4e07-a647-428a8c5a45c9","resolution":{"observed_at":"2026-08-05T10:41:04.020694Z","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":"2104.03617","last_updated":"2023-12-16T02:17:19Z","snapshot_observed_at":"2026-08-07T05:26:29.050197Z","submitted_at":"2021-04-08T08:57:13Z","title":"Half-Truth: A Partially Fake Audio Detection Dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03617","snapshot_observed_at":"2026-08-05T10:41:03.157874Z","title":"Half-truth: A par- tially fake audio detection dataset,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.157874Z"},"links":{"cited_paper":"/paper/2104.03617","citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:3349a68ad662195b82aeb955f66c4c27e5ac14ba6b1529375cc7a7dec5cf6fd4","observation_id":"d8b016ef-3e91-4a6a-86f6-4678777ab809","resolution":{"observed_at":"2026-08-05T10:41:03.157874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.02518","last_updated":"2021-06-15T15:41:34Z","snapshot_observed_at":"2026-07-06T10:56:54.885179Z","submitted_at":"2021-04-06T13:52:31Z","title":"An Initial Investigation for Detecting Partially Spoofed Audio","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.02518","snapshot_observed_at":"2026-08-05T10:41:03.170360Z","title":"An initial investigation for detecting par- tially spoofed audio,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.170360Z"},"links":{"cited_paper":"/paper/2104.02518","citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:1a84203f8edf4de8c81e9125e18fc715f33f98884b8731be889d109037b73674","observation_id":"37fe71e0-b5d7-454b-bb5b-97e609dd2fad","resolution":{"observed_at":"2026-08-05T10:41:03.170360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.14132","last_updated":"2021-08-31T16:02:58Z","snapshot_observed_at":"2026-08-04T14:34:08.635011Z","submitted_at":"2021-07-29T16:04:25Z","title":"Multi-Task Learning in Utterance-Level and Segmental-Level Spoof Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.14132","snapshot_observed_at":"2026-08-05T10:41:03.183317Z","title":"Multi-task learning in utterance-level and segmental- level spoof detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.183317Z"},"links":{"cited_paper":"/paper/2107.14132","citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:4ad4904bb21ebed8d76a93fa0a57455392f9497a45d81a76ea8e65402f2531b5","observation_id":"4f202525-3d7a-4595-98c7-0760ba8a38e7","resolution":{"observed_at":"2026-08-05T10:41:03.183317Z","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":"2026-08-05T10:41:03.959104Z","title":"Wav2vec 2.0: A framework for self-supervised learn- ing of speech representations,","venue":null,"work_id":"1177fc51-cec6-4871-8f70-b05b10d638ab","year":2020},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.196901Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:f8261cfa92431cc7519c277ac1e209ce3632ecaca4179c342f48712a3f3c1cb4","observation_id":"0664f477-0032-4e5a-a27a-b61aeb9593a8","resolution":{"observed_at":"2026-08-05T10:41:03.971546Z","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":"2026-08-05T10:41:03.923281Z","title":"The partialspoof database and countermeasures for the detection of short fake speech segments embedded in an utterance,","venue":null,"work_id":"dc62a023-4004-47f1-8d6b-af2eed050343","year":2022},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.206457Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:0b2ef292e18fa3392f1fb75b2b9cc3ba89f97c0adf78fa8f1d3299d16760c4c0","observation_id":"c3fe74b4-ca6f-4d2d-bfae-9e4482663157","resolution":{"observed_at":"2026-08-05T10:41:03.933340Z","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":"2026-08-05T10:41:03.867111Z","title":"Waveform boundary detection for partially spoofed audio,","venue":null,"work_id":"544ac695-2558-4c4e-bf12-69dc47a4bcdb","year":2023},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.216885Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:effc2535679cf2455e6f9c71c6a757309e0cb73de87cbc77ae8abb4ab68fdc57","observation_id":"e24abe07-14da-4949-9ece-964cf1701831","resolution":{"observed_at":"2026-08-05T10:41:03.891030Z","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":"2005.11184","last_updated":"2020-05-22T13:39:14Z","snapshot_observed_at":"2026-08-06T08:50:55.637766Z","submitted_at":"2020-05-22T13:39:14Z","title":"End-to-end Named Entity Recognition from English Speech","version":1},"cited_work":{"arxiv_id":"2005.11184","doi":null,"metadata_source":"pith","pith_arxiv_id":"2005.11184","snapshot_observed_at":"2026-08-05T10:41:03.493662Z","title":"End-to-end Named Entity Recognition from English Speech","venue":"cs.CL","work_id":"8e9fd58d-9bb9-4f34-8872-f619e85c8698","year":2020},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.231015Z"},"links":{"cited_paper":"/paper/2005.11184","citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:ca0a1b5ac514c3d833f3fbd54e7d3a38cab0699337984089b8eafc5f450557d7","observation_id":"f54a4bd4-d724-4682-a227-314575dc2d60","resolution":{"observed_at":"2026-08-05T10:41:03.512053Z","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":"2026-08-05T10:41:03.820408Z","title":"Robust speech recogni- tion via large-scale weak supervision,","venue":null,"work_id":"8362926a-f78b-4da9-95c2-7c0032ab5561","year":2023},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.256068Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:b79bf4f0248a8224f5be882ee96fa6690fc21e4ef82323cfdc64fb96c9c37ca3","observation_id":"d409d5da-f134-4994-930b-857a7807c864","resolution":{"observed_at":"2026-08-05T10:41:03.839315Z","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":"2026-08-05T10:41:03.777696Z","title":"Attention is all you need,","venue":null,"work_id":"b7cc0b9e-ad47-4b60-901a-a49f611885d8","year":2017},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.272787Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:4394a1193faf25b642364428bd11d12fed93045170eae1f5de1106e098b0db7b","observation_id":"0f6a390e-4d4e-49f2-bb48-1329b49ff70f","resolution":{"observed_at":"2026-08-05T10:41:03.786987Z","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":"2407.21611","last_updated":"2024-08-19T16:09:14Z","snapshot_observed_at":"2026-07-06T18:55:02.790902Z","submitted_at":"2024-07-31T13:49:17Z","title":"Enhancing Partially Spoofed Audio Localization with Boundary-aware Attention Mechanism","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21611","snapshot_observed_at":"2026-08-05T10:41:03.284513Z","title":"Enhancing partially spoofed audio localization with boundary-aware attention mech- anism,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.284513Z"},"links":{"cited_paper":"/paper/2407.21611","citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:9c676ce3260ffdef5abaf0e1951c00e4dad9acdbed65370967f3bfa163e138eb","observation_id":"23507646-c23d-4bb6-9dd9-bd773055a4e7","resolution":{"observed_at":"2026-08-05T10:41:03.284513Z","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":"2026-08-05T10:41:03.748547Z","title":"An efficient temporary deepfake location approach based embed- dings for partially spoofed audio detection,","venue":null,"work_id":"ee4bb6b7-be2e-4ce7-80ac-16f5ef358b98","year":2024},"citing_paper":{"arxiv_id":"2509.03829","last_updated":"2025-09-04T02:33:00Z","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T10:41:03.296949Z"},"links":{"citing_paper":"/paper/2509.03829"},"observation_digest":"sha256:5036768b3b8761d61a62dd3e0627434eddc29f699d5c1d388093c2bb96f616a2","observation_id":"74e271da-741a-4bb4-85af-cc1efdcc099e","resolution":{"observed_at":"2026-08-05T10:41:03.759275Z","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":"2509.03829","last_updated":"2025-09-04T02:33:00Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T08:23:57.643578Z","submitted_at":"2025-09-04T02:33:00Z","title":"NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":1,"verified_fuzzy":18},"total_outbound_references":24},"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 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2509.03829."}