{"as_of":"2026-08-07T06:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:429c79f221a13a5f88df9ca05f9bddb651dacd31c37e56452fdf8c1d1eaef44a","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T22:41:17.365335Z","state":"measured"},{"denominator":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2602.16305/citation-record","integrity":"/paper/2602.16305/integrity","json":"/paper/2602.16305/citation-record.json","paper":"/paper/2602.16305"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-02T22:41:16.642000Z","title":"Distilling the knowledge in a neural network.arXiv preprint arXiv:1503.02531,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.642000Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:2a9d4b8ef42f629e51a873a0e865de71888a9b70c03a524aae4418c718b8b725","observation_id":"906fbe31-597b-4837-86dc-343b74e9dc8a","resolution":{"observed_at":"2026-08-02T22:41:16.642000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1509.02971","last_updated":"2019-07-05T10:47:27Z","snapshot_observed_at":"2026-07-06T04:29:24.362640Z","submitted_at":"2015-09-09T23:01:36Z","title":"Continuous control with deep reinforcement learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1509.02971","snapshot_observed_at":"2026-08-02T22:41:16.699188Z","title":"P., Hunt, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.699188Z"},"links":{"cited_paper":"/paper/1509.02971","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:cc7499fd6fb1280525b04f185d6df2aa923c492fbb0d99c47fc56c23713a52b8","observation_id":"4a9fa353-b541-4e04-b809-66f2190659b2","resolution":{"observed_at":"2026-08-02T22:41:16.699188Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24901","last_updated":"2026-05-29T15:48:51Z","snapshot_observed_at":"2026-08-04T13:51:39.702206Z","submitted_at":"2025-09-29T15:11:18Z","title":"Unmute the Patch Tokens: Rethinking Probing in Multi-Label Audio Classification","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.24901","snapshot_observed_at":"2026-08-02T22:41:17.172433Z","title":"Unmute the patch tokens: Rethinking probing in multi-label audio classification","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:17.172433Z"},"links":{"cited_paper":"/paper/2509.24901","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:8a6b1d035916317808652ba96158c681c33fb1c72cb9bea24f2d0e42171000f7","observation_id":"6c12c591-c1b3-4fbe-ba14-1d56292205f6","resolution":{"observed_at":"2026-08-02T22:41:17.172433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.03022","last_updated":"2022-05-29T17:51:53Z","snapshot_observed_at":"2026-08-06T01:28:58.479299Z","submitted_at":"2022-03-06T18:13:09Z","title":"HEAR: Holistic Evaluation of Audio Representations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.03022","snapshot_observed_at":"2026-08-02T22:41:17.282492Z","title":"R., Raj, B., Schuller, B","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:17.282492Z"},"links":{"cited_paper":"/paper/2203.03022","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:bbc288d9f421d776fdec44031ea3821f66f5d17f2d679ce688d8af964494dfa2","observation_id":"911ade0b-cbe0-4050-94a5-258388592c9e","resolution":{"observed_at":"2026-08-02T22:41:17.282492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.03209","last_updated":"2018-04-09T19:58:17Z","snapshot_observed_at":"2026-07-06T06:32:32.083176Z","submitted_at":"2018-04-09T19:58:17Z","title":"Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.03209","snapshot_observed_at":"2026-08-02T22:41:17.365335Z","title":"Speech Commands: A Dataset for Limited- V ocabulary Speech Recognition.arXiv:1804.03209,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:17.365335Z"},"links":{"cited_paper":"/paper/1804.03209","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:f2b80fb95a2155cecfe0afb0cb3351b6e8dd64ccd595569266a73512fb4288a6","observation_id":"7591f2fb-ff44-4857-9b48-7cce12f5db5c","resolution":{"observed_at":"2026-08-02T22:41:17.365335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T22:41:17.026841Z","title":"Beyond [CLS]: Exploring the true potential of masked image modeling representations","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:17.026841Z"},"links":{"citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:f096bbf29797743928f84ed7b51a1abd11374a9eed737aa641d1f9cb7b82aa70","observation_id":"38931a61-f864-4c0f-945c-0d0cd712723f","resolution":{"observed_at":"2026-08-02T22:41:17.026841Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.06366","last_updated":"2022-10-03T11:47:10Z","snapshot_observed_at":"2026-08-04T18:14:09.239336Z","submitted_at":"2022-08-12T16:48:10Z","title":"BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.06366","snapshot_observed_at":"2026-08-02T22:41:16.967166Z","title":"Beit v2: Masked image modeling with vector-quantized visual tokenizers.arXiv preprint arXiv:2208.06366,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.967166Z"},"links":{"cited_paper":"/paper/2208.06366","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:98ad04a2410836ed939d0e2e262902ab3c6a58a899536ae43f23c2def879fd6d","observation_id":"0affb7cc-401b-4e19-923e-e8b29075326d","resolution":{"observed_at":"2026-08-02T22:41:16.967166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.12260","last_updated":"2022-04-26T12:32:10Z","snapshot_observed_at":"2026-08-07T05:19:10.506439Z","submitted_at":"2022-04-26T12:32:10Z","title":"Masked Spectrogram Modeling using Masked Autoencoders for Learning General-purpose Audio Representation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.12260","snapshot_observed_at":"2026-08-02T22:41:16.765942Z","title":"Masked spectrogram modeling using masked autoencoders for learning general-purpose audio repre- sentation.arXiv:2204.12260,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.765942Z"},"links":{"cited_paper":"/paper/2204.12260","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:1144d918064cfc011ededc14c69b1efee706402d0ea0423b670896ad2d9245ec","observation_id":"6118d71f-d3c9-4214-a546-2444cf67ddfc","resolution":{"observed_at":"2026-08-02T22:41:16.765942Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.04906","last_updated":"2022-01-28T12:23:37Z","snapshot_observed_at":"2026-07-06T11:08:17.373935Z","submitted_at":"2021-05-11T09:53:21Z","title":"VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.04906","snapshot_observed_at":"2026-08-02T22:41:16.534566Z","title":"Vicreg: Variance- invariance-covariance regularization for self-supervised learning.arXiv preprint arXiv:2105.04906,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.534566Z"},"links":{"cited_paper":"/paper/2105.04906","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:28b95af9fc1c6625508bfb91a5afeea1d536167c27422d95e3513f5566871570","observation_id":"b924d19e-6e7e-4de3-aea6-4e6feabdab7f","resolution":{"observed_at":"2026-08-02T22:41:16.534566Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14637","last_updated":"2024-09-23T00:31:39Z","snapshot_observed_at":"2026-07-06T19:19:37.350445Z","submitted_at":"2024-09-23T00:31:39Z","title":"Not Only the Last-Layer Features for Spurious Correlations: All Layer Deep Feature Reweighting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.14637","snapshot_observed_at":"2026-08-02T22:41:16.594200Z","title":"W., Nanfack, G., and Belilovsky, E","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.594200Z"},"links":{"cited_paper":"/paper/2409.14637","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:eaf5559fba067b2cc10fe2ecb0338c29e4647f40a55319236b9d117cda119826","observation_id":"c5e7b028-b8c8-423f-9818-e31779d8b4e2","resolution":{"observed_at":"2026-08-02T22:41:16.594200Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.01038","last_updated":"2019-04-01T18:05:02Z","snapshot_observed_at":"2026-08-06T00:26:50.886840Z","submitted_at":"2019-04-01T18:05:02Z","title":"fairseq: A Fast, Extensible Toolkit for Sequence Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.01038","snapshot_observed_at":"2026-08-02T22:41:16.873757Z","title":"fairseq: A fast, extensible toolkit for sequence modeling.arXiv:1904.01038,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:16.873757Z"},"links":{"cited_paper":"/paper/1904.01038","citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:7c99c1dfb5574187c1fbf68cdab66b534a5e066a404c7a6614734237bcfafbf9","observation_id":"8447544d-bb2f-4b48-85e1-77e672092be8","resolution":{"observed_at":"2026-08-02T22:41:16.873757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T22:41:17.084231Z","title":"Attention, please! revisiting attentive probing for masked image modeling.arXiv:2506.10178,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-02T22:41:17.084231Z"},"links":{"citing_paper":"/paper/2602.16305"},"observation_digest":"sha256:c4bf9ac1575e924851d60d85d844dd2c8d599af9670f14e5af1a626690b8fee2","observation_id":"f5dc7a81-6efe-45dc-89ef-658468777dc8","resolution":{"observed_at":"2026-08-02T22:41:17.084231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2602.16305","last_updated":"2026-05-29T15:57:02Z","latest_version":2,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-02T22:41:14.518887Z","submitted_at":"2026-02-18T09:37:20Z","title":"BAT: Better Audio Transformer Guided by Convex Gated Probing"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":12},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2602.16305."}