{"as_of":"2026-08-19T19:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7a849efcd23bd8d6505a771009b44dc60539f68346c14cccb59d6634ac382158","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:20:21.183845Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:20:21.088802Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T23:37:27.593053Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.16136","snapshot_observed_at":"2026-08-06T15:20:21.088802Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.088802Z"},"links":{"cited_paper":"/paper/2507.16136","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:011dbb51339634bf5f76e2ca524cb43ab11efd405a80d17a5d56c27817a28059","observation_id":"6cbe66de-5c2f-43ce-b4d9-955f512eeda0","resolution":{"observed_at":"2026-08-06T15:20:21.088802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"cited_work":{"arxiv_id":"2507.16136","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.16136","snapshot_observed_at":"2026-07-02T23:37:27.593053Z","title":"SDBench: A comprehensive benchmark suite for speaker diarization,","venue":null,"work_id":"38774d99-18a4-4d35-9217-cb43870384a8","year":2025},"citing_paper":{"arxiv_id":"2606.08505","last_updated":"2026-06-07T08:10:14Z","snapshot_observed_at":"2026-08-15T21:02:35.881887Z","submitted_at":"2026-06-07T08:10:14Z","title":"Fast and Robust On-Device Speaker Diarization: Relative Minimum Cluster Size for Stride-Accelerated Pipelines","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T18:05:41.144900Z"},"links":{"cited_paper":"/paper/2507.16136","citing_paper":"/paper/2606.08505"},"observation_digest":"sha256:34194e07451d1d6e3f7fba3c77c1a6c0f69595703e179026503ce687e0567bf6","observation_id":"371f3eb5-3148-40ac-b122-6d17ec55a105","resolution":{"observed_at":"2026-07-02T23:37:27.594616Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.16136/citation-record","integrity":"/paper/2507.16136/integrity","json":"/paper/2507.16136/citation-record.json","paper":"/paper/2507.16136"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.16136","snapshot_observed_at":"2026-08-06T15:20:21.088802Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.088802Z"},"links":{"cited_paper":"/paper/2507.16136","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:011dbb51339634bf5f76e2ca524cb43ab11efd405a80d17a5d56c27817a28059","observation_id":"6cbe66de-5c2f-43ce-b4d9-955f512eeda0","resolution":{"observed_at":"2026-08-06T15:20:21.088802Z","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":"2026-08-06T15:20:21.731834Z","title":null,"venue":null,"work_id":"7d0bec7d-de7c-4f77-b99d-d52008122b18","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.094724Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:35a5811373ee1e732897296db301014833544b21b37237d6343897af0fb37e8d","observation_id":"d2f7f853-482a-4c45-a705-9aba95464952","resolution":{"observed_at":"2026-08-06T15:20:21.734317Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.717655Z","title":"Figure 4 breaks down DER into 3 components: (i) Missed Detection, (ii) False Alarm, and (iii) Confusion","venue":null,"work_id":"a8d0c765-0843-41b2-b63e-397b6d6dfc45","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.100327Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:c938632327298ec46230173bddf8a0359c127ec3f6fa261d030d69a0e76dc12b","observation_id":"e04721c8-b084-485d-be86-4b61c74cc967","resolution":{"observed_at":"2026-08-06T15:20:21.720278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.709482Z","title":"To demonstrate its effectiveness, we developed SpeakerKit, an inference efficiency-optimized system built on Pyannote v3 that maintains low DER while achieving a 9.6x speedup","venue":null,"work_id":"20ce1f51-b6a3-47de-8c76-4c0feda24814","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.103033Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:ee782391a5be36c73eb49c070dc2e507fe0664d8228b09a66214a8f31e51267f","observation_id":"e17d2132-e5b3-4d9c-85b7-7ceb94237265","resolution":{"observed_at":"2026-08-06T15:20:21.712815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.702050Z","title":null,"venue":null,"work_id":"9a30ac73-c076-40dc-9ded-573310a61c2a","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.105650Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:70fb634e156bc8014d37a5d8e32e9272d1b77a637c69a46af99f964433b0c9ee","observation_id":"2972cc2f-699b-43c9-8dc9-b0708dcb015f","resolution":{"observed_at":"2026-08-06T15:20:21.704638Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.680852Z","title":"pyannoteai api,","venue":null,"work_id":"7126018a-38a7-46b5-886a-b88616b2817b","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.121709Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:90f3052a03e62481bd0d37f86d2fc5ecff0b783a0738325ec2b5333efe689c8b","observation_id":"1a9dfce9-2892-48f3-bb61-8a1321308dcc","resolution":{"observed_at":"2026-08-06T15:20:21.683214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.673762Z","title":"gladia api,","venue":null,"work_id":"dc0f9ec3-b662-46e3-8d65-9d7b6f30862b","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.123910Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:ad4cec5f1e6153cbeff0033ce40e33d8d2a17234a2e6ab2d340f9b0f1886be1c","observation_id":"aac6759e-8300-4442-b1a4-3806ff2cb447","resolution":{"observed_at":"2026-08-06T15:20:21.676137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.01477","last_updated":"2021-04-05T17:23:19Z","snapshot_observed_at":"2026-08-16T19:01:27.641666Z","submitted_at":"2020-12-02T19:33:44Z","title":"The Third DIHARD Diarization Challenge","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.01477","snapshot_observed_at":"2026-08-06T15:20:21.108230Z","title":"The third dihard diarization challenge,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.108230Z"},"links":{"cited_paper":"/paper/2012.01477","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:90d37865dc2909675aac4ab4d34b31bc7512f53f4d62f5942d25e840a29816cd","observation_id":"1bd98553-8fea-4872-983e-bc8997b80f6d","resolution":{"observed_at":"2026-08-06T15:20:21.108230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:20:21.111269Z","title":"The voxceleb speaker recognition challenge: A retrospective,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.111269Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:80415ebcc6752b705c98e24203dfe0add4fdb0114a6461eb987cb6f72be9b747","observation_id":"95920cc8-f0ee-4b62-abe1-518a612e6a42","resolution":{"observed_at":"2026-08-06T15:20:21.111269Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08887","last_updated":"2024-01-16T23:50:26Z","snapshot_observed_at":"2026-08-16T14:26:57.441963Z","submitted_at":"2024-01-16T23:50:26Z","title":"NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription","version":1},"cited_work":{"arxiv_id":"2401.08887","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.08887","snapshot_observed_at":"2026-08-06T15:20:21.447228Z","title":"NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription","venue":"cs.SD","work_id":"f2a82152-ed12-4158-8c51-f0becfe4cf30","year":2024},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.113765Z"},"links":{"cited_paper":"/paper/2401.08887","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:29e7b92b870fae2b7624bfb939f854ce3161bc26fac414c3bb76bf998dab2801","observation_id":"55dd473c-d19f-44b9-8002-653ed0d7040a","resolution":{"observed_at":"2026-08-06T15:20:21.450181Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.695050Z","title":"Powerset multi-class cross entropy loss for neural speaker diarization,","venue":null,"work_id":"cae0230d-9815-4b2f-9ff8-4063ac1f57e5","year":2023},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.116731Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:fe24676b4f33127dd434ae0d2f9e3209b017fcab8256e3fa9c77c0c48119ce3e","observation_id":"8931b29b-bb96-451e-bf37-4a316108edf5","resolution":{"observed_at":"2026-08-06T15:20:21.697482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.687911Z","title":"Amazon transcribe,","venue":null,"work_id":"e11ea58a-92ed-4ec6-8a5f-7198a9bf3f55","year":2023},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.119278Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:4c8be7d8bd70fb3d8048fc2ac609f6d2be2c6ce64eda363279197940a8bdf4b3","observation_id":"31273fb9-f8a4-4c7a-8fc1-d66c9e2f7263","resolution":{"observed_at":"2026-08-06T15:20:21.690284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.739154Z","title":null,"venue":null,"work_id":"8cf845d4-3dd3-4f7f-948d-f432a1410c72","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.092157Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:d6700356023cf870a4f39cf6d6474232c9183d22137062c629676b0913138703","observation_id":"2a9b8ca1-f45c-4ef7-a17f-1a7f3be2c131","resolution":{"observed_at":"2026-08-06T15:20:21.741263Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.622484Z","title":"Vbx: Speaker verification using bayesian inference,","venue":null,"work_id":"ebdb7ba6-02d8-42ae-b107-12f674924013","year":2021},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.140239Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:625b43748f8dcd2d759b85ba3ebf1b27b5519adbdff7d9366665e620f83cb3da","observation_id":"a1f42184-6a65-4b3d-b07d-03d1eeaf8422","resolution":{"observed_at":"2026-08-06T15:20:21.625150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.724854Z","title":null,"venue":null,"work_id":"d7d4596a-26d0-4c4d-a791-db1bd67f202f","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.097422Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:faa55a86d68a3af7534b51721c00cda8fe01dfd3d6f05ed7263b0b70558dd0a7","observation_id":"db215220-c977-4d0b-b105-83a3d9dbc78d","resolution":{"observed_at":"2026-08-06T15:20:21.727128Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.666481Z","title":"Deepgram,","venue":null,"work_id":"40f1c06a-1f4b-4122-8aec-028a1f3de66d","year":2023},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.126364Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:fc74dfc833ee5eabd2992838581c6f7db8e0b3e5f0b525e286966c9102bafef3","observation_id":"851dd771-c14d-4526-81df-08781954d345","resolution":{"observed_at":"2026-08-06T15:20:21.668774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.659837Z","title":"Picovoice sdk,","venue":null,"work_id":"10eedde0-f9f7-4ee7-877e-ac0e03d07eec","year":2023},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.128740Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:35d7a174beb6b2dd633017f5a14011763fb34a4d2ff8501659babb84d9af00ff","observation_id":"beb71267-6963-46b5-b086-32850a84effa","resolution":{"observed_at":"2026-08-06T15:20:21.662098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.652432Z","title":"Picovoice diarization benchmarks","venue":null,"work_id":"8ff04b3b-f07d-416e-b69c-49801b252194","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.130958Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:479877a2456dc222ecd586890328a6ff06b5f33af92ec5f1d44fbb8efed0a23c","observation_id":"84eaf422-28ae-4b8a-81b0-0df8951b7d14","resolution":{"observed_at":"2026-08-06T15:20:21.655357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.645281Z","title":"pyannote github issue","venue":null,"work_id":"a4e661d7-8df5-4e44-985e-6402d5f0800d","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.133146Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:2618b35e9f0f5a2aacc07b6c350e1c5ffe9bed95f65b6f970c24e42cfb30dba6","observation_id":"5cf5b464-ccc3-4a11-9aa0-a53e3a7d32af","resolution":{"observed_at":"2026-08-06T15:20:21.647797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.637855Z","title":"Pyannote github issue","venue":null,"work_id":"347b794b-3903-41a1-8ead-14bbd32a08ab","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.135832Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:b4787ba2e5eac0908b60e3bbed0a85bac4dd546206fcd9939a1c14d73639925a","observation_id":"93718d9a-42a7-45f3-a03f-45c8f5b5c167","resolution":{"observed_at":"2026-08-06T15:20:21.640704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.630386Z","title":"Nemo open source speaker diarization system","venue":null,"work_id":"e8197d63-1793-47da-a64f-58cb416f4594","year":2022},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.138050Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:6657a810ed6afe19707a8ae768cc4c31da7528708c8fd9cc27367fc7b67f44f5","observation_id":"70ebc734-681c-4ef6-b974-069d2220be34","resolution":{"observed_at":"2026-08-06T15:20:21.633074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.614916Z","title":"Callhome american english speech,","venue":null,"work_id":"b6800705-dc04-49f5-b2fe-d1dfaf323fa1","year":1997},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.142515Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:717a9f44c11b635e82fa599326325992d83e4fec6991ac6a1b0147cad15c0c82","observation_id":"1e25e56e-553a-4a2f-9b22-e0a3e8c0f221","resolution":{"observed_at":"2026-08-06T15:20:21.617334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.607494Z","title":"The third dihard diarization challenge,","venue":null,"work_id":"14acedd9-bf0b-4bfc-b512-619ad1c3aca4","year":2021},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.145016Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:b530a1308379b1001575ec99a9ce1cd4df0987807188a7e4aa732bde134ff311","observation_id":"0c18e726-21e0-43f5-9afe-f8d6c4b5980f","resolution":{"observed_at":"2026-08-06T15:20:21.610077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.11987","last_updated":"2022-11-10T18:59:00Z","snapshot_observed_at":"2026-08-08T11:23:49.984312Z","submitted_at":"2020-03-24T13:02:59Z","title":"Partially Observed Discrete-Time Risk-Sensitive Mean Field Games","version":2},"cited_work":{"arxiv_id":"2003.11987","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.11987","snapshot_observed_at":"2026-08-06T15:20:21.436743Z","title":"Partially Observed Discrete-Time Risk-Sensitive Mean Field Games","venue":"eess.SY","work_id":"85862e37-8fc7-4d1f-a089-da7562efa8d4","year":2020},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.147591Z"},"links":{"cited_paper":"/paper/2003.11987","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:7a1c8fe2f3683e45d5cd2a1985240dafbe360c5712314ccbb4b0837ebfc19740","observation_id":"8336499c-062b-4de5-98ec-ced0bba2cb5e","resolution":{"observed_at":"2026-08-06T15:20:21.439791Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:20:21.150302Z","title":"Earnings-21: A practical benchmark for asr in the wild,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.150302Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:a127f04fe28b1eef746f3d97b84ef6332fdde6f372dde966d39a5efad57acc04","observation_id":"4e34a6b7-929b-4ced-a6ce-bfc28e9329ad","resolution":{"observed_at":"2026-08-06T15:20:21.150302Z","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":"10.21437/interspeech.2022-10466","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Msdwild: Multi-modal speaker diarization dataset in the wild,","venue":"Interspeech 2022","work_id":"c8887c94-b29d-4e1a-aefe-8dd4a9ae0f50","year":2022},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.152924Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:f0550f8e5ce0698c0ba48cb69623bdf30af81b42876bdf231d1517bbbb9178f9","observation_id":"29ea3f18-4b12-4615-acca-f568634edad5","resolution":{"observed_at":"2026-08-06T15:20:21.211765Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.600057Z","title":"Announcing the ami meeting corpus,","venue":null,"work_id":"b1d60abb-8b11-4003-ac9b-837f4f71854f","year":2006},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.155317Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:689141fca6362b3e3a47424bf429d2996fb1d83bce47ed2821e0677d510141a7","observation_id":"dca47095-2e09-4a86-bbc8-e2fb8bec62ab","resolution":{"observed_at":"2026-08-06T15:20:21.602384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:20:21.157802Z","title":"Spot the conversation: Speaker diarisation in the wild,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.157802Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:a9ab3d235c8768b5c0cece0b81c16f8066e343e8dafc3c809df7ce0a9a0ec6ed","observation_id":"f46d468e-1a0d-4066-9d20-f224b41bd2ff","resolution":{"observed_at":"2026-08-06T15:20:21.157802Z","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":"2026-08-06T15:20:21.592237Z","title":"M2met: The icassp 2022 multi-channel multi-party meeting transcription challenge,","venue":null,"work_id":"043cb594-27df-4189-a9c2-6f46b1031d14","year":2022},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.160065Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:6692f5be28d9b34cfe7bc295568ea705dc45e13f7767cb59592337f6c2290ca3","observation_id":"26beb7d9-8d9e-4a5d-9c6b-1e2b550f4a9e","resolution":{"observed_at":"2026-08-06T15:20:21.594784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.560882Z","title":"Wespeaker: A research and production oriented speaker embedding learning toolkit,","venue":null,"work_id":"bcd54177-225a-46c7-bde7-64991d377e6a","year":2023},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.183845Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:803f64d22212cc231e5ee8e37755cda6d458bdc0862ee664bf31d95236d5f14c","observation_id":"ce029f9c-d923-4f9b-9153-27fce4f20b9f","resolution":{"observed_at":"2026-08-06T15:20:21.563720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.03603","last_updated":"2021-08-10T09:15:00Z","snapshot_observed_at":"2026-08-16T18:33:04.681788Z","submitted_at":"2021-04-08T08:38:44Z","title":"AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.03603","snapshot_observed_at":"2026-08-06T15:20:21.164907Z","title":"Aishell-4: An open source dataset for speech enhancement, separation, recognition and speaker diarization in conference scenario,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.164907Z"},"links":{"cited_paper":"/paper/2104.03603","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:571e4fdfa13a2b89e30a0afab5f43d30f0e8c59fc9138a0cb88fe8de30ed18c2","observation_id":"58de7ddd-1d98-4911-826d-deb27d7d004c","resolution":{"observed_at":"2026-08-06T15:20:21.164907Z","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":"2026-08-06T15:20:21.584028Z","title":"Speech recognition and multi-speaker diarization of long conversations,","venue":null,"work_id":"af75b521-73b3-48be-9bc8-09ecc6b482dd","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.167296Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:9f70b29f88ea9b8e2088257fa795c895f1333b3435fe1f07fab9764f33266127","observation_id":"803819f2-7c32-46cf-bdd8-890590a8ed52","resolution":{"observed_at":"2026-08-06T15:20:21.586756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"3161.35480","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:20:21.394674Z","title":"Ava-avd: Audio-visual speaker diarization in the wild,","venue":null,"work_id":"ce741f62-4706-47b6-8026-61faeea62a2e","year":2022},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.171756Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:245251a058e7c4cd37ebb8f8eebc534caac4209efe56b4796f043e46ae1044d7","observation_id":"c67ccfb4-a390-4a2e-bfa0-473dcf9fc5f5","resolution":{"observed_at":"2026-08-06T15:20:21.398781Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.01640","last_updated":"2022-06-01T18:02:45Z","snapshot_observed_at":"2026-08-19T18:37:48.082804Z","submitted_at":"2022-04-04T16:38:55Z","title":"APP: Anytime Progressive Pruning","version":2},"cited_work":{"arxiv_id":"2204.01640","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.01640","snapshot_observed_at":"2026-08-06T15:20:21.323967Z","title":"APP: Anytime Progressive Pruning","venue":"cs.LG","work_id":"6d09fe3c-c328-46ac-861a-afbbd652b8a3","year":2022},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.174227Z"},"links":{"cited_paper":"/paper/2204.01640","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:1fe84174e1fcf2fb516548647b4a3a4d374bb8f4224928d0da426a174ed6bce9","observation_id":"cb19bee7-5e13-463f-8762-262efa6dcb8c","resolution":{"observed_at":"2026-08-06T15:20:21.327130Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-06T15:20:21.576680Z","title":"Whiperkit","venue":null,"work_id":"892a9b54-d013-4f52-9620-9ffbcd7d14aa","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.176947Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:3ed6838cb6d697747dc26ce90c55327499f229bf53ad9b1543e4c0d35874e51a","observation_id":"190b4c01-e19b-418d-888c-40eacbdac348","resolution":{"observed_at":"2026-08-06T15:20:21.579145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:20:21.179123Z","title":"Wavlm: Large-scale self-supervised pre-training for full stack speech processing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.179123Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:d59d3f36f376fd7a7300b46907f207f361ae3b7edc81f342d4fcd4a037203450","observation_id":"063cd465-a267-4fe0-8443-f2ff959fc775","resolution":{"observed_at":"2026-08-06T15:20:21.179123Z","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":"2026-08-06T15:20:21.568945Z","title":"Huggingface","venue":null,"work_id":"a438f924-c47c-4c09-a49b-db9701779e6b","year":null},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.181219Z"},"links":{"citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:b7e341c58f003033432346faceb85197720604059e519fb5e0ce8fe79f600525","observation_id":"e830bfb6-e0e3-4a31-a523-ed8544ac3414","resolution":{"observed_at":"2026-08-06T15:20:21.571596Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.08072","last_updated":"2020-11-05T03:28:08Z","snapshot_observed_at":"2026-08-11T03:50:40.551159Z","submitted_at":"2020-05-16T19:29:33Z","title":"Speech Recognition and Multi-Speaker Diarization of Long Conversations","version":2},"cited_work":{"arxiv_id":"2005.08072","doi":null,"metadata_source":"pith","pith_arxiv_id":"2005.08072","snapshot_observed_at":"2026-08-06T15:20:21.406735Z","title":"Speech Recognition and Multi-Speaker Diarization of Long Conversations","venue":"eess.AS","work_id":"154c475e-7cd8-44f2-8329-362c90ceed46","year":2020},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.169386Z"},"links":{"cited_paper":"/paper/2005.08072","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:0541441a1a5fb394c1936c8907a6548f786e84d4b673c3bf8b70e3f7c9b9751f","observation_id":"15733d8c-0862-4f81-9876-f90e145de800","resolution":{"observed_at":"2026-08-06T15:20:21.410442Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.07393","last_updated":"2022-02-25T06:48:01Z","snapshot_observed_at":"2026-08-19T16:27:46.175502Z","submitted_at":"2021-10-14T14:27:41Z","title":"M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge","version":3},"cited_work":{"arxiv_id":"2110.07393","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.07393","snapshot_observed_at":"2026-08-06T15:20:21.425667Z","title":"M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge","venue":"cs.SD","work_id":"df09a3a7-3252-4107-becf-48a783b7f695","year":2021},"citing_paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:21.162341Z"},"links":{"cited_paper":"/paper/2110.07393","citing_paper":"/paper/2507.16136"},"observation_digest":"sha256:2276bb3798a536fae0db20328b60a60e83e1fe371ffcad9ee35a45a39fbd963b","observation_id":"592f6a26-0518-4a52-a81f-0d0e337ce1da","resolution":{"observed_at":"2026-08-06T15:20:21.428912Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.16136","last_updated":"2025-08-06T16:02:25Z","latest_version":2,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-18T10:30:25.303177Z","submitted_at":"2025-07-22T01:11:26Z","title":"SDBench: A Comprehensive Benchmark Suite for Speaker Diarization"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":1,"metadata_mismatch":5,"parse_uncertain":0,"unresolved":10,"verified_exact":2,"verified_fuzzy":21},"total_outbound_references":39},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2507.16136."}