{"as_of":"2026-08-19T14:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f8fbbaf0b18d3b66a6f7fe8c4906c65143229891b738080d2c050235d61806a2","coverage":[{"denominator":61,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":61,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:02:45.295621Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T22:11:44.891731Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2504.18582","doi":"10.48550/arxiv.2504.18582","metadata_source":"arxiv_reference","pith_arxiv_id":"2504.18582","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Taher and Ahmed, Sara Azad and Tariq, Kanar R","venue":"ArXiv.org","work_id":"cbfe9d5b-10b1-461a-8501-04ffd9c8f542","year":null},"citing_paper":{"arxiv_id":"2606.11219","last_updated":"2026-05-11T20:27:40Z","snapshot_observed_at":"2026-08-05T20:46:41.277498Z","submitted_at":"2026-05-11T20:27:40Z","title":"Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents","version":1},"reference_index":245,"source":"arxiv_source","source_observed_at":"2026-06-30T22:11:44.891731Z"},"links":{"cited_paper":"/paper/2504.18582","citing_paper":"/paper/2606.11219"},"observation_digest":"sha256:550d3b2ad7d2368b8dddf9c4d605d1e690c70f504b4d85c6aa4d29fa80040c54","observation_id":"33d140e9-adf6-41f4-8b1e-bcd7f04b8fcb","resolution":{"observed_at":"2026-06-30T22:15:05.584407Z","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/2504.18582/citation-record","integrity":"/paper/2504.18582/integrity","json":"/paper/2504.18582/citation-record.json","paper":"/paper/2504.18582"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T11:02:47.250420Z","title":"This work has gained significant importance in the field of speech processing","venue":null,"work_id":"e5b90a89-6a47-4d12-b2c3-3171e6e90451","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.769214Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:82c1fde7ba16420767d11f11fcaf9bf0ff799897849fd302aa5e2046e66b0c90","observation_id":"2eb515d7-8143-4cbf-8543-c645585f80df","resolution":{"observed_at":"2026-08-16T11:02:47.256123Z","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":"2026-08-16T11:02:47.218929Z","title":null,"venue":null,"work_id":"0565b736-95d5-461e-937c-cebeb472d78d","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.779460Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:aba4017bb57964b25f858cacaf10ccd342bda56430349c072675e499ca7dd73e","observation_id":"a8314ec0-d525-4c8b-8933-f2e1ed82fd46","resolution":{"observed_at":"2026-08-16T11:02:47.227098Z","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":"2026-08-16T11:02:47.194747Z","title":null,"venue":null,"work_id":"ca95ca98-1dfb-4f28-8af8-a6f2d5f0560d","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.793740Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:61182ea32677acf05b73a27244a2d6867cb124f0d5c288c5ea0687e7bf92c542","observation_id":"93e919b9-3a82-4ce8-ac0d-cb41589d4907","resolution":{"observed_at":"2026-08-16T11:02:47.203287Z","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":"2026-08-16T11:02:47.173914Z","title":"Finally, Conclusion and Future Work","venue":null,"work_id":"7ae09e9b-9821-4378-8e33-4a3b08e15040","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.804948Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:61c513e10defe0a5868d48a8c27bf8e1bd13f36a37ba0213232c098e2683bfed","observation_id":"91d64bf9-75f7-44ee-808e-9c96e65c1b1b","resolution":{"observed_at":"2026-08-16T11:02:47.181702Z","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":"2026-08-16T11:02:47.149294Z","title":"data augmentation","venue":null,"work_id":"bfba9cad-b762-4018-99eb-f09363607789","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.811113Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:e9e64f4bcb57e8f5a3693f67c67e87520cf10499aea7063d6375122d2303fb8d","observation_id":"afae7ea1-6d3d-4fd7-8939-5d7850214b0a","resolution":{"observed_at":"2026-08-16T11:02:47.157973Z","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":"2026-08-16T11:02:47.129049Z","title":"The approach starts by providing a comprehensive depiction of the dataset, including its organization and the preprocessing procedures executed to make it suitable for training","venue":null,"work_id":"93fee055-e559-4436-9694-3be2bac06f54","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.817096Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:b1a862c29b6cb93209146a44953e45400ea63c7d608df16dbca97ddbaf291b78","observation_id":"42b3e2f8-65f7-4a91-9472-27147b42d0fa","resolution":{"observed_at":"2026-08-16T11:02:47.134988Z","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":"2026-08-16T11:02:47.096042Z","title":"Ensuring the model's ability to differentiate between distinct voices was crucial, especially for recordings involving many speakers [41]","venue":null,"work_id":"c40fb3d8-e562-4fa1-bf34-d4fd0bf97c27","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.829251Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:66aa6a2e83c5d87dbb8e5610c33336f19e2a7c9050eb96440cbdb858ea6fc9c7","observation_id":"aad3470c-30c0-451d-b8c5-7f55865bf378","resolution":{"observed_at":"2026-08-16T11:02:47.109660Z","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":"2026-08-16T11:02:47.071568Z","title":"By normalizing the data, the model is able to prioritize the distinct attributes of each speaker's voice, without being affected by differences in volume [42]","venue":null,"work_id":"851f3a40-ff28-4a6c-a73f-1e825804946c","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.835013Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:3d5ee0501d5a901418e4b7b3f37a2deb4f42c0aee52acd6261e273f232610a1e","observation_id":"b0c17a5d-7989-428d-b0d3-e6f2d0dc1c81","resolution":{"observed_at":"2026-08-16T11:02:47.078930Z","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":"2026-08-16T11:02:47.044731Z","title":"Segmentation aids in the training of the model to identify shifts in speakers and enhances its capacity to process lengthy audio re cordings [1]","venue":null,"work_id":"6d7ae525-4cdf-48a4-8b8b-d41dd345e7a8","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.844236Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:da88f9482973005c8ef5aabc07db071019b8590319e4af94dd18b76452fe18fa","observation_id":"377f9d20-210e-4c19-adc9-68f06f6d12b9","resolution":{"observed_at":"2026-08-16T11:02:47.051234Z","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":"2026-08-16T11:02:47.010824Z","title":"These strategies enhance the model's resilience to various acoustic circumstances and speaker varianc es [43]","venue":null,"work_id":"5e5ed83e-de3e-405c-9520-8211d58a8dee","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.851874Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:1023ac992333933adc031426f34eee4d300617f2f01d79123c76bbdb5aa6f5ca","observation_id":"8530449a-c15b-4b19-8f04-0f986ede9e81","resolution":{"observed_at":"2026-08-16T11:02:47.020538Z","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":"2026-08-16T11:02:46.989503Z","title":null,"venue":null,"work_id":"213cd705-253d-4b71-85b4-9e9dbf0a4a6f","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.863151Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:d0068e7b890e35c3d7a4cbb87db8a54a5a99b23a0288285a47ffd278240e7fcd","observation_id":"f238edb9-5f57-4c99-ada2-e017c3ca4607","resolution":{"observed_at":"2026-08-16T11:02:46.995381Z","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":"2026-08-16T11:02:46.967795Z","title":null,"venue":null,"work_id":"4928c1d8-f3a5-45ff-ad90-2f7f66739461","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.873329Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:96bb39190e6279c6821980fc78dc337167ded9f7f3ae6186bbf7a0cccf7ed328","observation_id":"916cb460-6451-4af6-9a5c-14d0cc408d76","resolution":{"observed_at":"2026-08-16T11:02:46.974572Z","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":"2026-08-16T11:02:46.942382Z","title":"This change really considers practical situations where speakers may speak at different tempos in order to enhance the model for variation in time","venue":null,"work_id":"06f42b6f-d372-403c-9fec-fe20ba05b72f","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.884279Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:d5229085f4ce1672d187567db3eea0068bbf32d8725f0751e1e2b543c7acf767","observation_id":"ad37cf4d-a1c7-4986-afb7-1e0abe3d33b3","resolution":{"observed_at":"2026-08-16T11:02:46.950037Z","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":"2026-08-16T11:02:46.915048Z","title":"The initial learning rate was fixed at 1e -5 as set by previous experiments and adjusted with a constant cosine rate to obtain convergence","venue":null,"work_id":"285ea81c-1e90-40b9-8991-414f6e901ba7","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.891425Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:5b1e263a7f20ee050851b203063264198cac45fe17875fd4d770a0c8f5745646","observation_id":"c6285a77-4634-40a3-909a-681d9017df84","resolution":{"observed_at":"2026-08-16T11:02:46.924965Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"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":"2026-08-16T11:02:46.894445Z","title":null,"venue":null,"work_id":"2f0c400f-22f7-45cb-bd8d-a80ad95552e9","year":null},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.899887Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:e4ff1e5a7d10833f4e92b8f1b236cf0df40ae154b6df5180adc3e00fd7280a90","observation_id":"908e1fec-98c5-4cd6-9c06-374586cb29f7","resolution":{"observed_at":"2026-08-16T11:02:46.900849Z","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":"2026-08-16T11:02:46.873153Z","title":"A review of speaker diarization: Recent advances with deep learning,","venue":null,"work_id":"5ef921c3-4b6b-4fe5-b547-e2d7df11ee93","year":2022},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.913289Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:84096b9b12e243859e4cafd86455eaef6109cae994c9580e88364dec7f71d7f9","observation_id":"797d4d03-069a-4225-a87c-c6aa57f65707","resolution":{"observed_at":"2026-08-16T11:02:46.880861Z","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":"2005.09921","last_updated":"2020-10-05T07:12:42Z","snapshot_observed_at":"2026-08-17T12:28:42.326030Z","submitted_at":"2020-05-20T09:08:41Z","title":"End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.09921","snapshot_observed_at":"2026-08-16T11:02:44.924355Z","title":"End-to-end speaker diarization for an unknown number of speakers with encoder-decoder based attractors,","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.924355Z"},"links":{"cited_paper":"/paper/2005.09921","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:590fcc6a7a69f334e3629bb0552a2c11b046e3779d7467195f008e87a1a6ec82","observation_id":"23b5f647-b18e-484f-b359-787adc061e73","resolution":{"observed_at":"2026-08-16T11:02:44.924355Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.01983","last_updated":"2024-03-04T12:27:32Z","snapshot_observed_at":"2026-08-17T12:29:07.005037Z","submitted_at":"2024-03-04T12:27:32Z","title":"Language and Speech Technology for Central Kurdish Varieties","version":1},"cited_work":{"arxiv_id":"2403.01983","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.01983","snapshot_observed_at":"2026-08-16T11:02:45.736631Z","title":"Language and Speech Technology for Central Kurdish Varieties","venue":"cs.CL","work_id":"9bac3491-9f6c-483c-b47a-1f6239560ca2","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.935089Z"},"links":{"cited_paper":"/paper/2403.01983","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:3207528e3eb9cbcfd0025482510a2546ea4c0ea3d7c05e3feec64f346b410c84","observation_id":"a7c2dfbd-21bd-4f57-8334-6eb68e0bca9c","resolution":{"observed_at":"2026-08-16T11:02:45.743380Z","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":"2026-08-16T11:02:46.853579Z","title":"KuBERT: Central Kurdish BERT Model and Its Application for Sentiment Analysis,","venue":null,"work_id":"db42a71f-b925-4093-a3ba-aa9ee332c47e","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.948401Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:039a93023bea28a524edb6ecec454bd8b84dada06b240b05449b4308c439562b","observation_id":"6ebc924b-62b1-4bcf-a120-a269ab762567","resolution":{"observed_at":"2026-08-16T11:02:46.858862Z","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":"2026-08-16T11:02:46.833247Z","title":"wav2vec 2.0: A framework for self -supervised learning of speech representations,","venue":null,"work_id":"6aa7c1eb-ab88-4b66-9476-2f08dcc84954","year":2020},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.966133Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:77df6af9e28436f656c6b38349d8814bfd4828de133cc08ab969776b03dd5186","observation_id":"26fb66ae-5d77-4946-8a0d-c612e634bb73","resolution":{"observed_at":"2026-08-16T11:02:46.838612Z","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":"1904.05862","last_updated":"2019-09-11T08:19:49Z","snapshot_observed_at":"2026-08-17T12:28:40.241678Z","submitted_at":"2019-04-11T17:29:30Z","title":"wav2vec: Unsupervised Pre-training for Speech Recognition","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.05862","snapshot_observed_at":"2026-08-16T11:02:44.973306Z","title":"wav2vec: Unsupervised pre -training for speech recognition,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.973306Z"},"links":{"cited_paper":"/paper/1904.05862","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:92a5510cc02138ff50580b54c420fa519ae0c67a4d3a34b3b62fe30624e0ba1c","observation_id":"1a6f2899-cca5-46c4-9a03-c33486018c95","resolution":{"observed_at":"2026-08-16T11:02:44.973306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02561","last_updated":"2024-09-09T12:38:00Z","snapshot_observed_at":"2026-08-17T12:29:16.697856Z","submitted_at":"2024-04-23T10:47:56Z","title":"Breaking Walls: Pioneering Automatic Speech Recognition for Central Kurdish: End-to-End Transformer Paradigm","version":3},"cited_work":{"arxiv_id":"2406.02561","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.02561","snapshot_observed_at":"2026-08-16T11:02:45.673876Z","title":"Breaking Walls: Pioneering Automatic Speech Recognition for Central Kurdish: End-to-End Transformer Paradigm","venue":"eess.AS","work_id":"d3665d01-e29b-4d30-bddf-b72232de5271","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:44.991563Z"},"links":{"cited_paper":"/paper/2406.02561","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:1090fea9870a84fa60525cce6ebc6fe62089113a5af1a20208048e16d6a07cf4","observation_id":"60c6b99f-add4-4567-9527-bf4a62662ee0","resolution":{"observed_at":"2026-08-16T11:02:45.682821Z","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":{"arxiv_id":"2012.03411","last_updated":"2020-12-19T09:18:21Z","snapshot_observed_at":"2026-08-15T16:45:09.638988Z","submitted_at":"2020-12-07T01:53:45Z","title":"MLS: A Large-Scale Multilingual Dataset for Speech Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.03411","snapshot_observed_at":"2026-08-16T11:02:45.012822Z","title":"Mls: A large-scale multilingual dataset for speech research,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.012822Z"},"links":{"cited_paper":"/paper/2012.03411","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:5f896a5241f00a39a2b72fd94fbbe777129c45204c3d0fecf8495c36a8e41a1a","observation_id":"ab0895dc-91e1-45f2-8a06-475dd8da7ec3","resolution":{"observed_at":"2026-08-16T11:02:45.012822Z","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":"2026-08-16T11:02:46.814701Z","title":"Deep Learning for Natural Language Processing in Low -Resource Languages,","venue":null,"work_id":"52e4b0f7-ad64-455b-8883-0dec69922cc5","year":2020},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.020760Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:54e82b8258e3722ba51f84882887ddfbcbc81379b809cf5d5b091c028bed2022","observation_id":"f46ace2e-1554-410f-b9ed-7e4ab603cc3a","resolution":{"observed_at":"2026-08-16T11:02:46.819976Z","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":"2026-08-16T11:02:46.783783Z","title":"A survey on text classification: From traditional to deep learning,","venue":null,"work_id":"0cc87e30-20c0-44a6-b15f-3d3bec72c9a6","year":2022},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.028795Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:8a924f2e43dc65b06bd3f63e5c388bce58a203311bf6e678c2cd53ec563fcaf5","observation_id":"a524bea6-a8fc-4868-9448-0a37a570b069","resolution":{"observed_at":"2026-08-16T11:02:46.791280Z","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":"2010.12309","last_updated":"2021-04-09T13:48:02Z","snapshot_observed_at":"2026-08-18T14:05:17.455420Z","submitted_at":"2020-10-23T11:22:01Z","title":"A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.12309","snapshot_observed_at":"2026-08-16T11:02:45.036126Z","title":"A survey on recent approaches for natural language processing in low -resource scenarios,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.036126Z"},"links":{"cited_paper":"/paper/2010.12309","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:98875b5f8292edbce7af61ae45675df712bcf06a4af6611313ec74e291697d25","observation_id":"263e43c5-37b4-4112-89a1-6b137a903c29","resolution":{"observed_at":"2026-08-16T11:02:45.036126Z","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":"2026-08-16T11:02:46.764763Z","title":"Central Kurdish Automatic Speech Recognition using Deep Learning,","venue":null,"work_id":"1d48c1b9-ec1a-4acb-b7ae-705c0e5252f3","year":2022},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.042926Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:0c7e8d268cc12b8e8de3f2d7d001160395cb870c966b26d0ad2054d3e5510147","observation_id":"0463ba69-c635-424a-95a7-316b376e0608","resolution":{"observed_at":"2026-08-16T11:02:46.770633Z","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":"2026-08-16T11:02:46.740628Z","title":"Enhancing speaker diarization with large language models: A contextual beam search approach,","venue":null,"work_id":"4e00f56a-522c-41ac-93c2-3dc3b1e21c39","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.054001Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:8497a4c750338d5574aedbcfaa72c58897dcfaf6304b3966a87e7464b5404136","observation_id":"598ac89c-81e6-4180-962a-664b5bf9f289","resolution":{"observed_at":"2026-08-16T11:02:46.747285Z","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":"2026-08-16T11:02:46.714434Z","title":"2019 YEAR IN REVIEW: MACHINE LEARNING IN HEALTHCARE,","venue":null,"work_id":"166f0748-4f62-4b08-a17a-53341f926ebb","year":2019},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.060642Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:d115b52972ae2f8ffbd90b94fafbd7f06a65817a852d40d629d60b2cf0e06e81","observation_id":"54a77b2a-db78-4133-ab7a-cf962dba7d29","resolution":{"observed_at":"2026-08-16T11:02:46.722856Z","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":"2026-08-16T11:02:46.692708Z","title":"Speaker diarization: A review of recent research,","venue":null,"work_id":"c753aaff-83c1-4765-b41c-64120daf7d33","year":2012},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.068731Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:009d6b428fd00016c9e636be7e9ac07700acf2c17a3cbabb3dd10e13d3f34386","observation_id":"4f996201-96ed-4be9-b459-65df95d2e2ed","resolution":{"observed_at":"2026-08-16T11:02:46.698177Z","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":"2026-08-16T11:02:46.664288Z","title":"Approaches and applications of audio diarization,","venue":null,"work_id":"5da32996-3536-4867-8814-cfc56f4c44f1","year":2005},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.076618Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:f415dcfcc44168372f2b5254e4739317a45df01ea642194e68524e22afd8c94f","observation_id":"d829861e-eb41-4eff-be62-b0530ef2a4c0","resolution":{"observed_at":"2026-08-16T11:02:46.673655Z","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":"2026-08-16T11:02:46.638340Z","title":"Speaker diarization with PLDA i-vector scoring and unsupervised calibration,","venue":null,"work_id":"3c8d4773-37a6-4224-8544-ac298116a0ff","year":2014},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.083410Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:c0ebd4e52ae71d943326a37d516cd824231a13c2dfaa29dcba2bd5666efcbe7b","observation_id":"63654576-0401-4471-8554-6b448b961cd9","resolution":{"observed_at":"2026-08-16T11:02:46.644618Z","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":"2026-08-16T11:02:46.617722Z","title":"Speaker diarization with LSTM,","venue":null,"work_id":"328a761c-542a-4b26-aa1e-183b9fad669c","year":2018},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.094220Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:017b58e934c2430730e6a6eb4df22ec6d8d56d92d17fac9ff267285eb92efa0f","observation_id":"4a0aebe7-201a-48de-a762-b1a959ecb8ef","resolution":{"observed_at":"2026-08-16T11:02:46.625972Z","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":"2026-08-16T11:02:46.592272Z","title":"FocusNet: imbalanced large and small organ segmentation with an end -to-end deep neural network for head and neck CT images,","venue":null,"work_id":"c8776f17-1e32-4c8a-b53c-59d6df7456be","year":2019},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.101093Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:d440190b44a29dbfc059a87f1e4103cc13987db29953bf1cc80fd7bd3e3ef1fa","observation_id":"dd8eb248-529a-4a8d-b38d-17d29bd67ee3","resolution":{"observed_at":"2026-08-16T11:02:46.604307Z","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":"2026-08-16T11:02:46.549483Z","title":"End -to-end neural speaker diarization with self-attention,","venue":null,"work_id":"efe2bfd5-3db4-43ce-8d1a-e065c384d522","year":2019},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.106180Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:4d0a8f8c0202b9774e20b20484942d8b331064836c306b5af2faa187e381f83c","observation_id":"26873f2f-37a2-439c-a622-11b828ef5a69","resolution":{"observed_at":"2026-08-16T11:02:46.569184Z","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":"2026-08-16T11:02:45.119657Z","title":"The third DIHARD diarization challenge,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.119657Z"},"links":{"cited_paper":"/paper/2012.01477","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:3ccf22af1d935e97392d4f7611aa1c839619170be6658cb3a89f878c4e35ea0c","observation_id":"c3684d9b-e1ad-47f1-b58f-f6c8023b4edf","resolution":{"observed_at":"2026-08-16T11:02:45.119657Z","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":"2026-08-16T11:02:46.519643Z","title":"Automatic speech recognition for under -resourced languages: A survey,","venue":null,"work_id":"0cd47246-2e48-4245-8ac9-ea3fac36f221","year":2014},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.126378Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:ac546cd0f82bab5e1f4a747bad9a4c1efb4190a9375b5a788d0e0c3f3847eb35","observation_id":"fcc2cb36-56df-411a-9ae4-9c78222834cb","resolution":{"observed_at":"2026-08-16T11:02:46.529282Z","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":"2026-08-16T11:02:46.494296Z","title":"Advances in Deep Speaker Verification: a study on robustness, portability, and security,","venue":null,"work_id":"64837ab7-e046-4be7-940d-fd115159e1a3","year":2023},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.133588Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:2f784264819298d3557553e413f4db8cabcc4e8ea8a884f1493d6e5ab8fedb5c","observation_id":"20f9abba-355a-4e50-a32e-f73996aa8f84","resolution":{"observed_at":"2026-08-16T11:02:46.504126Z","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":"2026-08-16T11:02:46.461567Z","title":"Towards end -to-end speaker diarization with generalized neural speaker clustering,","venue":null,"work_id":"3296fad9-df41-47ea-8f6b-1351777f0042","year":2022},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.138546Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:3f09970926e9cb4100be1929e6e4d56118bf3a8126cec668bf9b9343b29bbc5e","observation_id":"193f301f-b27e-4475-b444-378f4744168a","resolution":{"observed_at":"2026-08-16T11:02:46.471010Z","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":"2104.01295","last_updated":"2021-04-03T02:19:50Z","snapshot_observed_at":"2026-08-17T12:28:39.829214Z","submitted_at":"2021-04-03T02:19:50Z","title":"Equity Impacts of Dollar Store Vaccine Distribution","version":1},"cited_work":{"arxiv_id":"2104.01295","doi":null,"metadata_source":"pith","pith_arxiv_id":"2104.01295","snapshot_observed_at":"2026-08-16T11:02:45.436370Z","title":"Equity Impacts of Dollar Store Vaccine Distribution","venue":"econ.GN","work_id":"dbb3c1b3-b9b5-4a84-956a-ab81918dbf01","year":2021},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.147812Z"},"links":{"cited_paper":"/paper/2104.01295","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:a76f5bada8f5ba07e6569df0ac1fd5cf8f464f2a3e5019783a02d4aa804178a3","observation_id":"60c153b0-9fd3-45ac-93c0-bb0e815b9d3c","resolution":{"observed_at":"2026-08-16T11:02:45.446006Z","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":"2026-08-16T11:02:46.438554Z","title":"Kurdish interdialect machine translation,","venue":null,"work_id":"6677760a-da85-4cb7-bac0-c6e39c234ee6","year":2017},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.154395Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:fea4d05ab74e62492ff4a70c797bb54bfce004fddd30f9e8f59e940ceeeca214","observation_id":"62b674be-9213-4349-a18d-f6addc78eaca","resolution":{"observed_at":"2026-08-16T11:02:46.445377Z","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":"2026-08-16T11:02:46.415840Z","title":"Jira: a Central Kurdish speech recognition system, designing and building speech corpus and pronunciation lexicon,","venue":null,"work_id":"918bc01a-4441-4aeb-80ce-b6c4d1d4675b","year":2022},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.160399Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:8eb18a529537a805132eee0898bb21a09f9966a9ab12d5e47e4282d8c4f8c69b","observation_id":"cf12cdd8-180e-44f9-a90b-905eaefee436","resolution":{"observed_at":"2026-08-16T11:02:46.423290Z","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":"2026-08-16T11:02:46.393901Z","title":"Kurdish dialect recognition using 1D CNN,","venue":null,"work_id":"6266c173-e92a-4af2-86e7-cf893e616dda","year":2021},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.169268Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:6df4b2fe0d1c28a01c331c30da59dace38e614cbab5e4b7086e5c6a64abb811c","observation_id":"d0aea66f-bb6b-4a8e-a003-8cfc67715e2e","resolution":{"observed_at":"2026-08-16T11:02:46.400779Z","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":"2026-08-16T11:02:46.203771Z","title":"Effectiveness of self -supervised pre-training for asr,","venue":null,"work_id":"489cbc78-b809-4304-a32d-1dd4591cbcbf","year":2020},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.178468Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:4e37793b6a14c7fdb9bb08535fea2561f20382c3ebe8a0786b6b09202139c97b","observation_id":"0ba15c5d-3610-433b-ae78-1e0a0ee22b6c","resolution":{"observed_at":"2026-08-16T11:02:46.381125Z","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":"2012.06185","last_updated":"2021-01-14T14:17:22Z","snapshot_observed_at":"2026-08-16T18:59:18.891143Z","submitted_at":"2020-12-11T08:22:23Z","title":"Exploring wav2vec 2.0 on speaker verification and language identification","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.06185","snapshot_observed_at":"2026-08-16T11:02:45.184624Z","title":"Exploring wav2vec 2.0 on speaker verification and language identification,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.184624Z"},"links":{"cited_paper":"/paper/2012.06185","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:e73fe4273520f9715ff22c4bdab1bbb7756342d1fe4f6455a4bf57fe50753286","observation_id":"5c037890-6ca6-439e-bd9a-b53a6cb41cb8","resolution":{"observed_at":"2026-08-16T11:02:45.184624Z","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":"2026-08-16T11:02:46.176462Z","title":"EEND-SS: Joint end-to-end neural speaker diarization and speech separation for flexible number of speakers,","venue":null,"work_id":"5f25e866-626f-4366-b787-f0e972cd70ba","year":2022},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.193334Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:01a9301c6d64b00f18d08154aff389597df613fb9be51d3509403804d6eb2f3b","observation_id":"31932d37-cfd9-438a-a736-2f7e99c13b8d","resolution":{"observed_at":"2026-08-16T11:02:46.183388Z","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":"2026-08-16T11:02:46.143359Z","title":"MSFNet: Multi-Scale Fusion Network for Brain -Controlled Speaker Extraction,","venue":null,"work_id":"fd21369a-11fa-46c7-90d8-0edc105ffb34","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.202244Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:b4ab45cc46e6baf9c2036707e8061ea07bd061704c3210abb0dd7700b6070600","observation_id":"8d90d1aa-2357-4c04-a9a1-40b37869c19c","resolution":{"observed_at":"2026-08-16T11:02:46.149526Z","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":"2006.13979","last_updated":"2020-12-15T23:19:19Z","snapshot_observed_at":"2026-08-13T17:50:33.934751Z","submitted_at":"2020-06-24T18:25:05Z","title":"Unsupervised Cross-lingual Representation Learning for Speech Recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.13979","snapshot_observed_at":"2026-08-16T11:02:45.211539Z","title":"Unsupervised cross -lingual representation learning for speech recognition,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.211539Z"},"links":{"cited_paper":"/paper/2006.13979","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:c27f7c8162c561efbdc9733f127612f8b4ddebadffca399260fc656264e5c0b2","observation_id":"750af1d8-cc94-4e41-96f2-3612f7c2ba95","resolution":{"observed_at":"2026-08-16T11:02:45.211539Z","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":"2026-08-16T11:02:46.115672Z","title":"A survey on transfer learning,","venue":null,"work_id":"993d1b4f-9a0d-477d-a01b-45ac7596e234","year":2009},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.218910Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:3b0beeddf225e58d6c23ba072f34937c74bb57a6f9bbccc3a7f62e08cb41a041","observation_id":"d1686c16-39d3-4d4c-bf0d-fa5be58ec367","resolution":{"observed_at":"2026-08-16T11:02:46.122331Z","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":"2007.04239","last_updated":"2020-05-31T21:52:31Z","snapshot_observed_at":"2026-08-17T12:29:58.084943Z","submitted_at":"2020-05-31T21:52:31Z","title":"A Survey on Transfer Learning in Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.04239","snapshot_observed_at":"2026-08-16T11:02:45.226247Z","title":"A survey on transfer learning in natural language processing,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.226247Z"},"links":{"cited_paper":"/paper/2007.04239","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:c00f2037e0c02562ddc8782062638309f9b8e694f3f74f4857a632277c920dc3","observation_id":"adc4ae1e-f191-4032-9676-dfc275e1a9d5","resolution":{"observed_at":"2026-08-16T11:02:45.226247Z","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":"2026-08-16T11:02:46.085100Z","title":"The NIST speaker recognition evaluation program,","venue":null,"work_id":"954f4009-e969-44ba-ba2e-b5773231c1bf","year":2005},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.235036Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:34550ef19189353c5ac171b2ee6df251fc73daa6caf1dc5dab84a432216b5baf","observation_id":"58396a1e-17ff-48ff-8e54-42c707ecf82a","resolution":{"observed_at":"2026-08-16T11:02:46.094437Z","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":"2026-08-16T11:02:46.061445Z","title":"NSGA-II-DL: Metaheuristic optimal feature selection with Deep Learning Framework for HER2 classification in Breast Cancer,","venue":null,"work_id":"df876a93-b5ac-47d9-a692-2dfe60340dcd","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.242241Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:937780076231e183a4d2f41d4b7982f4550e36cef29a63bae1b14c7632a9e2d9","observation_id":"5315e7ee-620a-4f24-b4d4-eaaa95af1b29","resolution":{"observed_at":"2026-08-16T11:02:46.069478Z","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":"2026-08-16T11:02:46.035113Z","title":"Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge,","venue":null,"work_id":"8380317f-7984-434f-97f6-5027bc1ea841","year":2018},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.248431Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:37895cfd1095e8ef62666ccc54937c7429e20d05929502b9f4f919fd6a1e8c96","observation_id":"3d4e4e14-876e-48d8-a264-c1fb27d5449d","resolution":{"observed_at":"2026-08-16T11:02:46.041674Z","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":"2407.01963","last_updated":"2024-09-12T15:40:02Z","snapshot_observed_at":"2026-08-17T12:29:34.434079Z","submitted_at":"2024-07-02T05:42:32Z","title":"Towards Unsupervised Speaker Diarization System for Multilingual Telephone Calls Using Pre-trained Whisper Model and Mixture of Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2407.01963","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.01963","snapshot_observed_at":"2026-08-16T11:02:45.522578Z","title":"Towards Unsupervised Speaker Diarization System for Multilingual Telephone Calls Using Pre-trained Whisper Model and Mixture of Sparse Autoencoders","venue":"eess.AS","work_id":"52a77fe0-dd36-47ac-8706-e114d5aab1f9","year":2024},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.253584Z"},"links":{"cited_paper":"/paper/2407.01963","citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:32878f33be6a029f1c83ca23d0e3cc0d33cd7f579aa1e106e3edc1479d997290","observation_id":"336b51ff-8e4f-4c3e-9fb6-0ec71b6a040e","resolution":{"observed_at":"2026-08-16T11:02:45.541329Z","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":"2026-08-16T11:02:46.000837Z","title":"Audacity (R): Free audio editor and recorder [Computer application]. Version 3.0. 0 retrieved March 17th, 2021,","venue":null,"work_id":"bf119379-d16c-4e78-9b47-b1f3bb9e0c0f","year":2021},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.258320Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:82b5b6a0f850649fd0e423d233501707b08519511dd2d20554500e8880229139","observation_id":"7e0038d7-a6c0-4b8a-ba35-d1b9261bb7d9","resolution":{"observed_at":"2026-08-16T11:02:46.009047Z","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":"2026-08-16T11:02:45.976538Z","title":"Praat: doing phonetics by computer [Computer program],","venue":null,"work_id":"a294ee11-d866-4991-bcc5-9ec7b4e41181","year":2011},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.265982Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:f65fb37b35b0db1f21b42b552d28c58a66de19277b14bd1a188a99716fa4c3a8","observation_id":"6c62941f-bd99-4c8a-9378-dd7c71d7b6a5","resolution":{"observed_at":"2026-08-16T11:02:45.983477Z","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":"2026-08-16T11:02:45.934057Z","title":"Audio augmentation for speech recognition,","venue":null,"work_id":"7378a97e-2c8e-427f-a604-4fae4d2d2ac0","year":2015},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.271703Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:554265407a04cc4d60a2a344e01362e73e41212c5134efb7c96ea6615661cd07","observation_id":"6da349ea-d173-4231-84bd-e75d96ed07a0","resolution":{"observed_at":"2026-08-16T11:02:45.942794Z","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":"2026-08-16T11:02:45.903131Z","title":"Improving language understanding by generative pre -training,","venue":null,"work_id":"9604cb53-a0b4-4038-b464-4a5323fba46a","year":2018},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.277444Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:b92af9776f470de018981e2ea214e7ef23761b6bb5ce85a601b994a90151052a","observation_id":"e8b710ed-84e4-4d74-b5dd-d9a9ddb2ba7a","resolution":{"observed_at":"2026-08-16T11:02:45.910867Z","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":"2026-08-16T11:02:45.874141Z","title":"Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks,","venue":null,"work_id":"6017dab7-fbe4-497d-a2c0-2a3350a31806","year":2006},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.283715Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:8a12b27c42bbc4e5a7da2389aa078c23e4824c4d8d62803a45a2dea6f8eaa4e3","observation_id":"859475a3-0141-459f-8dd1-601ff34ca817","resolution":{"observed_at":"2026-08-16T11:02:45.880305Z","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":"2026-08-16T11:02:45.842514Z","title":"Topic segmentation with an aspect hidden Markov model,","venue":null,"work_id":"f7c01471-7e6d-429d-a4ef-381c5358340a","year":2001},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.289240Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:89533080e22b3353c693f57ab695e93846d68fe615e9a31024f03ae1c772ebf6","observation_id":"f1e0e054-0469-43ee-bf53-945cf134f878","resolution":{"observed_at":"2026-08-16T11:02:45.849828Z","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":"2026-08-16T11:02:45.808718Z","title":"Dropout: a simple way to prevent neural networks from overfitting,","venue":null,"work_id":"5b83c00d-025c-4360-bf66-dee69e939483","year":1929},"citing_paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-16T11:02:45.295621Z"},"links":{"citing_paper":"/paper/2504.18582"},"observation_digest":"sha256:d2de028b41f280a3451fc28cc56c8de30dbbc5a0dd99a351af7dc12978998a9b","observation_id":"a7153bfd-b60d-425f-812f-a0b956d43022","resolution":{"observed_at":"2026-08-16T11:02:45.816852Z","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"}}],"paper":{"arxiv_id":"2504.18582","last_updated":"2025-04-23T10:45:59Z","latest_version":1,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-17T12:14:43.782575Z","submitted_at":"2025-04-23T10:45:59Z","title":"Speaker Diarization for Low-Resource Languages Through Wav2vec Fine-Tuning"},"reference_resolution":{"displayed":61,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":4,"verified_fuzzy":43},"total_outbound_references":61},"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 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2504.18582."}