{"as_of":"2026-08-18T12:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b4db6bd61bd731783a1727905d1707c4380848264a8bbf5a38ec53f80b62c32a","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T19:43:33.402366Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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":"2026-06-26T11:33:32.067771Z","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":"2026-07-04T12:29:51.697896Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"cited_work":{"arxiv_id":"2502.05356","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05356","snapshot_observed_at":"2026-07-04T12:29:51.697896Z","title":"Distillation and Pruning for Scal- able Self-Supervised Representation-Based Speech Quality As- sessment,","venue":null,"work_id":"5ae0d0b2-516f-4ab6-b08d-f9e70f8b777a","year":2025},"citing_paper":{"arxiv_id":"2606.21933","last_updated":"2026-06-20T08:00:12Z","snapshot_observed_at":"2026-08-13T02:50:42.628158Z","submitted_at":"2026-06-20T08:00:12Z","title":"ISCSLP 2026 CoT-TTS Challenge: Chain-of-Thought Reasoning for Context-Aware Text-to-Speech","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-26T11:33:32.067771Z"},"links":{"cited_paper":"/paper/2502.05356","citing_paper":"/paper/2606.21933"},"observation_digest":"sha256:c61c8a1a80aaac32ee6cb9078d2d55e648a036f653577d772d8ea70760193a15","observation_id":"2ec7a0cc-dba3-45be-8661-d969736993b5","resolution":{"observed_at":"2026-07-04T08:29:42.169028Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"cited_work":{"arxiv_id":"2502.05356","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05356","snapshot_observed_at":"2026-07-04T12:29:51.697896Z","title":"Distillation and Pruning for Scal- able Self-Supervised Representation-Based Speech Quality As- sessment,","venue":null,"work_id":"5ae0d0b2-516f-4ab6-b08d-f9e70f8b777a","year":2025},"citing_paper":{"arxiv_id":"2606.23332","last_updated":"2026-06-22T13:41:24Z","snapshot_observed_at":"2026-08-04T14:09:25.194252Z","submitted_at":"2026-06-22T13:41:24Z","title":"Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-26T06:49:46.425849Z"},"links":{"cited_paper":"/paper/2502.05356","citing_paper":"/paper/2606.23332"},"observation_digest":"sha256:1245c9332645f71123a8fbab87a2acd45e9116d5ced5e8ad87f1ce9d6e236d26","observation_id":"fb71144c-0b83-4897-9564-67f4e1a4a8ab","resolution":{"observed_at":"2026-07-04T12:29:51.699304Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.05356/citation-record","integrity":"/paper/2502.05356/integrity","json":"/paper/2502.05356/citation-record.json","paper":"/paper/2502.05356"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T19:43:34.605899Z","title":"Non-intrusive speech quality assessment using neural networks,","venue":null,"work_id":"6e528f73-4d7a-40b6-a84f-e276041fb157","year":2019},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:32.945007Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:a4c5ae2ff475debf370ff73d212a442b183ac60007235b22809fa4d9b06ae776","observation_id":"984e3842-edb0-4272-82d3-118672bdee01","resolution":{"observed_at":"2026-08-08T19:43:34.625552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.595202Z","title":"Dnsmos: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,","venue":null,"work_id":"9982dcf2-8c58-468d-bcff-872b429ae2a6","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:32.948814Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:5e8ee59c150b5f32c32de26625f7e9c1f776934a02851c603d559a98cf5a264a","observation_id":"d3832161-2aeb-46d5-a872-6338f6daa252","resolution":{"observed_at":"2026-08-08T19:43:34.599675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.585002Z","title":"NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets,","venue":null,"work_id":"e136965a-037e-4bf9-9bbe-b28953324da7","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:32.952622Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:8118f680c1d9f3bdb051d35ca34799dffcb8d2138062718889488d716a031700","observation_id":"5c4e95bd-f9b6-4de6-9087-0a79ec7c8005","resolution":{"observed_at":"2026-08-08T19:43:34.588782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.574457Z","title":"Utilizing Self-Supervised Representations for MOS Prediction,","venue":null,"work_id":"3910eac1-e623-4277-92dd-ce290ef38a04","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:32.956206Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:47a60f28e443faa857e3c9e69a79b005a3a536d920720bd833fb0231139ebe7c","observation_id":"0f094d11-75ad-4e40-8e8e-6197dc4d0822","resolution":{"observed_at":"2026-08-08T19:43:34.578285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.565502Z","title":"wav2vec 2.0: A framework for self-supervised learning of speech representations,","venue":null,"work_id":"06e1fdf2-6ec6-4161-94ec-52f102e662f8","year":2020},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:32.982620Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:db6b849ddc9c2c2826fdcd29ebf5fd4a26f8c8a114d4b7fd57c405f56b377c8c","observation_id":"f7779210-3141-43ff-8855-92ce852ea0be","resolution":{"observed_at":"2026-08-08T19:43:34.568390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.556223Z","title":"Deep learning-based non-intrusive multi-objective speech assessment model with cross-domain features,","venue":null,"work_id":"11c9f368-b2ea-4d34-975b-a5ce7c38abd8","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.050052Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:61ac46cfadee91be075117f41e7e92294249d1a5bd158ec561fa1956bd193fa0","observation_id":"14c25693-df06-4e66-b87e-2b040c79595c","resolution":{"observed_at":"2026-08-08T19:43:34.559127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.547029Z","title":"Hubert: Self-supervised speech representation learning by masked prediction of hidden units,","venue":null,"work_id":"f4c13b9e-39ef-4239-86ac-ef257d44c76d","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.087716Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:edc54a78e5f56b4dd2c6141a246b522592c722d0b7a42568b1167ac40ffa0db5","observation_id":"7619af06-f29b-41b0-8ed8-78acecee589e","resolution":{"observed_at":"2026-08-08T19:43:34.549852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.537402Z","title":"UTMOS: UTokyo-SaruLab System for V oiceMOS Challenge 2022,","venue":null,"work_id":"ea7edd74-a747-482c-9603-ccb60e90a7f0","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.141039Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:847e7524a5b870662c19cb2982e5bda6f93f2189e7fe272bc79a3c7a0d93120d","observation_id":"63a7ff39-63a5-4f67-8ae3-06caff32f95d","resolution":{"observed_at":"2026-08-08T19:43:34.541485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.527128Z","title":"The voicemos challenge 2022,","venue":null,"work_id":"655cd124-e232-4060-ad59-4722d98327b4","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.185610Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:2dc8a308531c8ab227db6b4e065bb9ccae5e7629904451d042e028f56b8a4ed2","observation_id":"5d99567d-bf44-4490-b1c6-f0e8b74a84d5","resolution":{"observed_at":"2026-08-08T19:43:34.530913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.474462Z","title":"Analysis of XLS-R for speech quality assessment,","venue":null,"work_id":"55023660-0ec2-4111-a89b-2b24c5bbaa19","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.202988Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:1ae3a5277999e4d2ddf76b3e5e9b08890367226b493d0c0b5dd5d3dd547cc637","observation_id":"20978d2d-69bd-48c5-b477-b38f880bad41","resolution":{"observed_at":"2026-08-08T19:43:34.513469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.338728Z","title":"XLS-R: Self-supervised Cross-lingual Speech Rep- resentation Learning at Scale,","venue":null,"work_id":"98cca270-f30f-4208-bbc6-422e7950a1b1","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.216637Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:d714abddad4dbead2ed0b9c9ecfec28aa9ad71181c64453b2df3345b498a17f3","observation_id":"bf27408f-01a9-4493-abdb-addd6e014cf3","resolution":{"observed_at":"2026-08-08T19:43:34.401397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.249440Z","title":"ConferencingSpeech 2022 Challenge: Non-intrusive Objective Speech Quality Assessment (NISQA) Challenge for Online Conferencing Applications,","venue":null,"work_id":"253966a9-7c6a-4eee-8148-92d61ba14cb6","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.219569Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:54f4bcec8ffb2aefde02653e93bc34ff93f5a18455db3ed284758ca19d5b4ff4","observation_id":"e33b6530-f4d4-48d5-9da7-55156d2218db","resolution":{"observed_at":"2026-08-08T19:43:34.286250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00282","last_updated":"2024-02-01T02:15:59Z","snapshot_observed_at":"2026-08-16T14:22:40.660929Z","submitted_at":"2024-02-01T02:15:59Z","title":"PAM: Prompting Audio-Language Models for Audio Quality Assessment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00282","snapshot_observed_at":"2026-08-08T19:43:33.223187Z","title":"PAM: Prompting audio-language models for audio quality assessment,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.223187Z"},"links":{"cited_paper":"/paper/2402.00282","citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:b602b9bde2190bbde62da280235ee461d378e38e7ac697ce87f6fa3bbeab41e3","observation_id":"c8cbb901-8e7a-4887-b53e-fc9d2c10c66e","resolution":{"observed_at":"2026-08-08T19:43:33.223187Z","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":"2026-08-08T19:43:34.177408Z","title":"CLAP: Learning audio concepts from natural language supervision,","venue":null,"work_id":"0ea45ef9-d303-4488-add9-b40949ad7b94","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.227000Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:ff7824c6bf4d04f0006b5728624d099d8b5556377ce293731da9ee879df40d1b","observation_id":"625d43d1-7018-46c1-94ec-9d13b3e33e26","resolution":{"observed_at":"2026-08-08T19:43:34.202815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.151745Z","title":"DNN No-Reference PSTN Speech Quality Prediction,","venue":null,"work_id":"040c6efd-1fda-4c5a-8229-15e03fe83d38","year":2020},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.230521Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:d84fded4392d8932183c9191b0eab411eb07025e8698aa154d081442a3d0d6f9","observation_id":"dcc58df8-02c6-4643-9ba8-911c716d3113","resolution":{"observed_at":"2026-08-08T19:43:34.154843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.142157Z","title":"ICASSP 2021 deep noise suppression challenge,","venue":null,"work_id":"a397ee6a-f2df-4f78-8358-e0d413bfb153","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.233603Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:5e21f51ca15c3c8e220542bc786bcd021660028cc4bb6cd5d6bcc301773b96eb","observation_id":"e8d058c6-b67f-4793-92c4-8b6fb8d7b840","resolution":{"observed_at":"2026-08-08T19:43:34.145580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.132570Z","title":"Interspeech 2022 audio deep packet loss concealment challenge,","venue":null,"work_id":"a99086f7-4c38-4581-bd5a-a40f58ae2b8b","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.236428Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:784dfb1494300e98eaebd1ccfec9cb9f05e8ff4a830c4831cc1967ee4c262d94","observation_id":"2da41cfa-4079-45ca-aad0-28cbe904e645","resolution":{"observed_at":"2026-08-08T19:43:34.135928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.122819Z","title":"ICASSP 2023 speech signal improvement challenge,","venue":null,"work_id":"251025d9-d0b5-47aa-ab00-3ac73364a658","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.239815Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:064f27cff26184e7c5c566d093ac536be7451d7de919cf83bff47bf53586f3db","observation_id":"6bda20b3-854b-4514-b36b-8835862f1af4","resolution":{"observed_at":"2026-08-08T19:43:34.126494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.113867Z","title":"Protocol for the collection of databases of recordings for forensic-voice-comparison research and practice,","venue":null,"work_id":"207fa08c-22a7-46e8-8317-eff7d1b60230","year":2012},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.242868Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:cea9a118f1eed6163c34a6137069bad348aa07b441f232f0b740bf89b23f9277","observation_id":"a9966b67-7a3f-41b0-bcdb-124256c2a439","resolution":{"observed_at":"2026-08-08T19:43:34.116837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.103274Z","title":"Tcd-voip, a research database of degraded speech for assessing quality in voip applications,","venue":null,"work_id":"daa64f72-a998-40e5-809c-316259638730","year":2015},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.246003Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:df13a08a452a15a17fa462abb5be133293836e72a90f3c2e8113e62296e2c4a2","observation_id":"81640dbc-96f6-4c3b-a9a5-c9ed7713d649","resolution":{"observed_at":"2026-08-08T19:43:34.107326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.092349Z","title":"Speech quality factors for traditional and neural- based low bit rate vocoders,","venue":null,"work_id":"9897fa6a-b983-4113-9467-691dffa40c3a","year":2020},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.249163Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:39177ad65422e579cd125405e5d8f7485852ee594b28f319086a501e873fc8fd","observation_id":"b1486a6a-3722-4bf0-8f84-df10f2be82a0","resolution":{"observed_at":"2026-08-08T19:43:34.096279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.082769Z","title":"The blizzard challenge 2023,","venue":null,"work_id":"893046a4-ccde-4f55-b880-19728781acb2","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.251940Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:667fcd4e0b982a985bf5727c5ae8fbd7ec44168214f81f7540cb9c41a609d43c","observation_id":"00d2e5ab-5a58-4f50-af6f-7dbf0ae3bb00","resolution":{"observed_at":"2026-08-08T19:43:34.086095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.072554Z","title":"Interspeech 2021 deep noise suppression challenge,","venue":null,"work_id":"bb8302fa-141a-4a01-ac43-3370fe7a6c7c","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.254776Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:8a58f4fff6b307a01f003b8241413a8fc4097c9ff5b4b4100f0af1623f324685","observation_id":"06b20e7d-1588-4fe5-a25a-d89bc6c28c25","resolution":{"observed_at":"2026-08-08T19:43:34.076199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.061414Z","title":"The ICASSP 2024 audio deep packet loss concealment grand challenge,","venue":null,"work_id":"39b1352b-d915-4ed2-a7ab-cd30b1dd6a3d","year":2024},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.257649Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:54f9537253de86f2233be8bcf9558172a1c311209357657f2b5c5ab9e5027730","observation_id":"0fd99a06-ef19-4837-94f4-090528df4d57","resolution":{"observed_at":"2026-08-08T19:43:34.065346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:34.004512Z","title":"ICASSP 2024 speech signal improvement challenge,","venue":null,"work_id":"432e7931-81e2-4a54-8941-28e011a21ffd","year":2024},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.261386Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:1bf20bb7d5c8a3d742910fbb083807c91c53b225beda95a0a84e48ec35d99a4d","observation_id":"3d204079-9e06-407c-9e57-e1f0342edff2","resolution":{"observed_at":"2026-08-08T19:43:34.038989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.264663Z","title":"Decoupled weight decay regularization,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.264663Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:4f1ad17150d6d30710be67ad5bf06ff5c2ddc472a4d1d84d088434dee9bb0ba4","observation_id":"234308cb-9dae-4e06-a372-aa5c783dbbd8","resolution":{"observed_at":"2026-08-08T19:43:33.264663Z","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":"2026-08-08T19:43:33.907317Z","title":"Bias-aware loss for training image and speech quality prediction models from multiple datasets,","venue":null,"work_id":"1dd08b77-3290-48d7-92f6-25f328576765","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.268022Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:905b28c4159361e1e90ffb8c550644da4c0e669ea8b16cfd50f38726499a694a","observation_id":"cf348730-94ae-41ab-ab80-81cd2b094213","resolution":{"observed_at":"2026-08-08T19:43:33.950483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.813764Z","title":"Coqui TTS,","venue":null,"work_id":"f41dd842-a022-4b9b-8027-192d14580ca8","year":2021},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.271085Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:7f1686cf71882d976320e5f83bca724b56196efb2a7b6831c686fa731028536c","observation_id":"4846985e-5716-4d04-8b0f-11fdc87a4d49","resolution":{"observed_at":"2026-08-08T19:43:33.859732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.751915Z","title":"MultiSubs: A large-scale multimodal and multilingual dataset,","venue":null,"work_id":"b565486d-3898-41ac-b9e4-a1b800d1e24c","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.274545Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:34c3cc281eb14c15dcfc97ae27d5b269a559494cbdaab1a3e27cec034e0f145f","observation_id":"efadacc3-f5b8-4f51-94d8-952cf732360f","resolution":{"observed_at":"2026-08-08T19:43:33.763937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.742579Z","title":"ICASSP 2022 deep noise suppression challenge,","venue":null,"work_id":"628a8aba-1202-4594-8f32-2a67cbc3e6c1","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.277210Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:ead33b1bd8e1091c30225556d36bbed44162ec4da66c7b431f74d800e60bb628","observation_id":"b7a8985a-286c-40ea-803e-9e5b5366ef8a","resolution":{"observed_at":"2026-08-08T19:43:33.745970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.733227Z","title":"Deepfilternet: Perceptually motivated real-time speech enhancement,","venue":null,"work_id":"286ab6a5-6717-460f-b42e-8504b73b7783","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.279982Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:2fdd58c10ec623c2ce0d1b693410ee4a4579b672845171bf43a3c18efab72cf1","observation_id":"0eadc82b-c415-4650-93e8-bca1b9751427","resolution":{"observed_at":"2026-08-08T19:43:33.736209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.723456Z","title":"Data augmentation and loss normalization for deep noise suppression,","venue":null,"work_id":"d5a88100-ce8e-461f-8d49-cadaef0a876a","year":2020},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.283232Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:e4994173016fc344eca68b863280d868f8d656a6baf90d8dccdc51258cf0213f","observation_id":"d0d02e1a-ae05-4169-b9ee-5f50beda2167","resolution":{"observed_at":"2026-08-08T19:43:33.726579Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.713801Z","title":"Real time speech enhancement in the waveform domain,","venue":null,"work_id":"3553d85e-9a6f-47e7-be11-abfd79480a6a","year":2020},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.286165Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:65ca25574580f5aa0228559ce36ef2265bd672c55ca15238ddfe3e388edcfbf8","observation_id":"10ce886a-1ba2-4ec9-ac84-1d8e16216347","resolution":{"observed_at":"2026-08-08T19:43:33.717232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.289576Z","title":"timsainb/noisereduce: v1.0,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.289576Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:98c06c7cfdbbe756ba3523d7ef0b93109cea6e152feb5d2ef55bdd23afc9c03a","observation_id":"97bd0b74-b55b-4e08-9e7f-0b874f91e24f","resolution":{"observed_at":"2026-08-08T19:43:33.289576Z","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":"2026-08-08T19:43:33.703734Z","title":"Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis,","venue":null,"work_id":"c9e8a28e-6efa-4b55-8a41-112dc710a750","year":2020},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.293286Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:a8061d87b35f89a9ca6e396bb5b6cfefe82ed7a62ee630a4d731fa198997dcf8","observation_id":"beec576b-396a-49e3-bc9c-3e524f345f78","resolution":{"observed_at":"2026-08-08T19:43:33.707451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.693519Z","title":"LPCNET: Improving neural speech synthesis through linear prediction,","venue":null,"work_id":"27b858e2-05e8-4ab6-a8e8-56de38d29881","year":2019},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.296233Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:ecf325c20c605fc2d4783fd56fa1ed291520473a38f0b19e1a9304f74ec086f8","observation_id":"208fe748-ba1e-4ed7-8b23-4982f3369f12","resolution":{"observed_at":"2026-08-08T19:43:33.697366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.683228Z","title":"High-quality, low-delay music coding in the Opus codec,","venue":null,"work_id":"826efeda-bdab-4a59-b7fb-819e2e43ff63","year":2013},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.299835Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:6b31d20589f6eb68e27a9d5db3bc36f468b9ac957fff2471fb96cae80e9af248","observation_id":"230cf298-d446-49a7-968a-199771bc258d","resolution":{"observed_at":"2026-08-08T19:43:33.686790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.672343Z","title":"High fidelity neural audio compression,","venue":null,"work_id":"de4a3f1c-73f5-49cd-9413-527827c5eed7","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.302695Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:0c6ac4d27768d0ddffcf2c73ae8fdf45c1f3f293cd85fdcf7957c8274add18f8","observation_id":"8f312ca1-d929-4a04-aeb6-0f6f525efa4a","resolution":{"observed_at":"2026-08-08T19:43:33.676166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.662187Z","title":"Effect of noise suppression losses on speech distortion and asr performance,","venue":null,"work_id":"0020283b-60ce-4cc2-a1e1-c46872a465cf","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.305921Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:0edbcc979dd14d4a8fa8d73f195751907769b260ccc1ac94ea9dc8b3ead52562","observation_id":"f520b62a-9348-4fd5-b366-9a68ded2e3e6","resolution":{"observed_at":"2026-08-08T19:43:33.665340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.651498Z","title":"Importance estimation for neural network pruning,","venue":null,"work_id":"b5124c44-19ff-4be3-8ac8-706d8eaf6502","year":2019},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.308647Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:ba48c088e6bdfbe53b45b7587bd500cb1d38a461d96518e91e0ff9f1595fee95","observation_id":"69b71717-5b64-4c06-8161-7d2eca6ca5a8","resolution":{"observed_at":"2026-08-08T19:43:33.655032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.571662Z","title":"Dnsmos p.835: A non-intrusive perceptual objective speech quality metric to evaluate noise suppressors,","venue":null,"work_id":"ed0f3a72-4b7e-4d93-a193-9bf41ef384b0","year":2022},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.315733Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:3dfaeb30584c1e8bdf17db04581e7257218130ecd8bf81b889050afb697a398e","observation_id":"5901f9fc-c5d5-4420-be81-546260fd3e2d","resolution":{"observed_at":"2026-08-08T19:43:33.621328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-08T19:43:33.492852Z","title":"Torchaudio-squim: Reference-less speech quality and intelligibility measures in torchaudio,","venue":null,"work_id":"8e31c050-2896-4cc8-9e2b-aa830115be6a","year":2023},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.368413Z"},"links":{"citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:6850cecf41d4dc6f4109b59e6b4281374dc8c4b047413cf33cccdf238a2c5aba","observation_id":"eaac26f2-2a17-4590-8bf6-ae8e28ee66c3","resolution":{"observed_at":"2026-08-08T19:43:33.538530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.09574","last_updated":"2019-02-25T19:18:40Z","snapshot_observed_at":"2026-08-15T00:50:07.769538Z","submitted_at":"2019-02-25T19:18:40Z","title":"The State of Sparsity in Deep Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.09574","snapshot_observed_at":"2026-08-08T19:43:33.402366Z","title":"The state of sparsity in deep neural networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-08T19:43:33.402366Z"},"links":{"cited_paper":"/paper/1902.09574","citing_paper":"/paper/2502.05356"},"observation_digest":"sha256:27f140f8132e457457b45b55644a87d031d5a0f69f22797c42d531e705182768","observation_id":"b8b55980-8ed0-4bd2-9495-955ee0c8f340","resolution":{"observed_at":"2026-08-08T19:43:33.402366Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.05356","last_updated":"2025-02-07T22:08:12Z","latest_version":1,"primary_category":"eess.AS","snapshot_observed_at":"2026-08-15T18:43:24.196588Z","submitted_at":"2025-02-07T22:08:12Z","title":"Distillation and Pruning for Scalable Self-Supervised Representation-Based Speech Quality Assessment"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":39},"total_outbound_references":43},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2502.05356."}