{"as_of":"2026-08-10T01:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:65e1109360feda4f34158184219bed6d424b294199c1091ab9542ebadb58df9f","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:28:35.807111Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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":"2026-08-06T20:28:31.282921Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T20:28:36.324978Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"cited_work":{"arxiv_id":"2507.02666","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.02666","snapshot_observed_at":"2026-08-06T20:28:36.324978Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","venue":"cs.SD","work_id":"a41e1ebe-46d4-45cc-87d4-aac4f5771946","year":2025},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.282921Z"},"links":{"cited_paper":"/paper/2507.02666","citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:4a03babd786158a21c1742fb77a98a8707f42cd2269bad598ce4d622c8c1ca75","observation_id":"8dafb6f8-cc68-4304-a0d1-eb76830be4ab","resolution":{"observed_at":"2026-08-06T20:28:36.496175Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.02666/citation-record","integrity":"/paper/2507.02666/integrity","json":"/paper/2507.02666/citation-record.json","paper":"/paper/2507.02666"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:28:43.377585Z","title":null,"venue":null,"work_id":"2ab89d03-a883-4339-ad9a-2af126e7572b","year":null},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.222335Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:d750b6423d3d369e1a94ebf8ef1d0df4fd9575597a143097df8f6e8df4314d9a","observation_id":"a749fecc-7a27-45e6-9c7b-5514bbc48342","resolution":{"observed_at":"2026-08-06T20:28:43.464366Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"cited_work":{"arxiv_id":"2507.02666","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.02666","snapshot_observed_at":"2026-08-06T20:28:36.324978Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","venue":"cs.SD","work_id":"a41e1ebe-46d4-45cc-87d4-aac4f5771946","year":2025},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.282921Z"},"links":{"cited_paper":"/paper/2507.02666","citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:4a03babd786158a21c1742fb77a98a8707f42cd2269bad598ce4d622c8c1ca75","observation_id":"8dafb6f8-cc68-4304-a0d1-eb76830be4ab","resolution":{"observed_at":"2026-08-06T20:28:36.496175Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:43.101868Z","title":null,"venue":null,"work_id":"fbd4c799-063f-4858-9568-c9713cc4f485","year":null},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.374781Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:7bd31df9776c7d407a87cb57135167079f1fc1a043593bdc2597b56223d24caf","observation_id":"8ca7fc68-4b68-45e5-91e1-66db08b608a8","resolution":{"observed_at":"2026-08-06T20:28:43.206079Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:42.874756Z","title":"-” indicates that the data was not reported in the original paper. “Acc","venue":null,"work_id":"7bf3a187-5ab7-4552-9015-e149cf8d2b1b","year":null},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.461180Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:d8d94a752d332e4936e492135c4a8871746288819cd3104ca388d73bbba619e9","observation_id":"8f10dea6-8666-491c-9049-e7098317f556","resolution":{"observed_at":"2026-08-06T20:28:42.989121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:42.627193Z","title":"By defining such irrelevant information as noise and drawing inspiration from differential denoising techniques, we design a dual-softmax based differential attention mecha- nism","venue":null,"work_id":"b092d69d-d31f-4f4a-b9e4-1cc3deaee743","year":null},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.558065Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:638f8d8dad7ebb6944b355704315aab77fae0e13400ba27dbc07d6be65f25c98","observation_id":"bb4cc9e5-9692-47bf-91cb-eae6a01f1a7b","resolution":{"observed_at":"2026-08-06T20:28:42.757882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:42.383669Z","title":"Masked autoencoders are scalable vision learners,","venue":null,"work_id":"ab06284c-dc70-4018-bc8b-cbd3d5022aaa","year":2022},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.668474Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:7c0995af9e0d1e99615a1f56f93f949a5ddfbe98d56c42b61d58dff5edd55d52","observation_id":"6f538e54-0c0f-4588-9658-9d86361c4b8e","resolution":{"observed_at":"2026-08-06T20:28:42.503940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:42.171585Z","title":"Bert: Pre- training of deep bidirectional transformers for language under- standing,","venue":null,"work_id":"7c0e00c9-4627-4588-a44b-cb83abac025e","year":2019},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.830515Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:de9cc9e09fb18fcfa3b2276cd2ca76b87c7d5d3169f7aaf88ac50562c2999617","observation_id":"cb7bb7a5-687c-489b-9427-ec7f04d91678","resolution":{"observed_at":"2026-08-06T20:28:42.272561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00387","last_updated":"2024-08-31T08:33:13Z","snapshot_observed_at":"2026-07-06T19:08:39.942067Z","submitted_at":"2024-08-31T08:33:13Z","title":"Progressive Residual Extraction based Pre-training for Speech Representation Learning","version":1},"cited_work":{"arxiv_id":"2409.00387","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.00387","snapshot_observed_at":"2026-08-06T20:28:36.007990Z","title":"Progressive Residual Extraction based Pre-training for Speech Representation Learning","venue":"eess.AS","work_id":"9f0601a2-e505-4edc-9d18-1f0e3278d14e","year":2024},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:31.948048Z"},"links":{"cited_paper":"/paper/2409.00387","citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:ec78c744250cd4b51539b2c697f93a6607ff6edfda98009b5ae5e70294c92727","observation_id":"c90a53b3-3f9b-4d52-a3c8-4c4a2ac19a4a","resolution":{"observed_at":"2026-08-06T20:28:36.139009Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:41.931456Z","title":"Hubert: Self-supervised speech rep- resentation learning by masked prediction of hidden units,","venue":null,"work_id":"e5c0075e-62c8-4c0f-8f04-f82db83309e6","year":2021},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:32.126260Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:4c8a7f7d444af4c337461f8d7d172c0625f25ac9d6c9d461fb38da24b9f1080f","observation_id":"da253594-02a9-487a-9236-2eee7d372e6d","resolution":{"observed_at":"2026-08-06T20:28:42.063611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:41.707495Z","title":"wav2vec 2.0: a framework for self-supervised learning of speech representa- tions,","venue":null,"work_id":"8b621a87-fe16-4b95-997b-07302698ddae","year":2020},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:32.274563Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:c3b13590c14ac1ad1f2dd1d5369519e1511aa0898aeba1c65ad7d4d06862e10d","observation_id":"afcfbcf2-0914-44a5-8298-845b3c00c2ec","resolution":{"observed_at":"2026-08-06T20:28:41.831381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:41.472770Z","title":"Ssast: Self- supervised audio spectrogram transformer,","venue":null,"work_id":"862f3001-efee-490b-b12f-7b4485a7dfda","year":2022},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:32.430571Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:71d688d3b897ebfbd417755f56c1707798c1371199f6bef06e1f08bf1e19fb18","observation_id":"04d63030-e970-49ec-babb-1162d4c6c91a","resolution":{"observed_at":"2026-08-06T20:28:41.577894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:41.231516Z","title":"Masked autoencoders that listen,","venue":null,"work_id":"8e323681-a3e2-4619-8b19-21aa796ab0ba","year":2022},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:32.634714Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:d8e34a0e7fe8be5f8489f0e404048c25f45167e9b05615149b39ac3fa77570a3","observation_id":"914af37c-28fd-4eef-81e5-259442407311","resolution":{"observed_at":"2026-08-06T20:28:41.335845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:40.998399Z","title":"Efficient self- supervised learning with contextualized target representations for vision, speech and language,","venue":null,"work_id":"ca4690d0-6c04-4019-a6ea-956f217126bd","year":2023},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:32.783169Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:fcdceb298d155ded8998e851d36463b2945edc63a0bec367e3e6a3d0b3104fce","observation_id":"2e8b71a1-1d16-4412-9e65-d3949fa990f4","resolution":{"observed_at":"2026-08-06T20:28:41.083573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:40.811527Z","title":"Eat: Self- supervised pre-training with efficient audio transformer,","venue":null,"work_id":"228fb95c-fe57-4d50-b7b6-a10c49cad54f","year":2024},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:32.923679Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:07ac7935744eaecf9f54b8265ae6ab5c8c87295a9ea8f32463c0942fb5ff22e7","observation_id":"3fa660ad-9dd4-4021-80a0-1acf8c125bbf","resolution":{"observed_at":"2026-08-06T20:28:40.897608Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:40.589705Z","title":"Attention is all you need,","venue":null,"work_id":"6fd1755d-7eb1-4895-84ba-49c1d9479dd0","year":2017},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.071139Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:0fe96681dc8fe94d9b81ec0e34104fb26cd5875da0aafa78bb297f5dda2cb343","observation_id":"5e0203c3-3d5c-4f14-afd8-44f521a4dbb9","resolution":{"observed_at":"2026-08-06T20:28:40.704767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:40.367774Z","title":"Beats: audio pre-training with acoustic tokeniz- ers,","venue":null,"work_id":"1a54a801-58a3-4d65-bae9-968a3bd43946","year":2023},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.192286Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:699791b5d82aa887be85176facb48315af5d519018b59b576bca0113556e4e09","observation_id":"d7eaaa9e-0c11-4765-bca9-c51b03c39380","resolution":{"observed_at":"2026-08-06T20:28:40.458739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:40.184491Z","title":"An image is worth 16x16 words: Transform- ers for image recognition at scale,","venue":null,"work_id":"389e7cf6-b3ab-469b-99bc-2cd8252e33a3","year":2021},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.345089Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:518d72ffd36fb0170d4409aec06fe527cb63ddd553ba515807eb051c6cec10f1","observation_id":"b81b1671-74d8-4721-b57c-f1d863b62c55","resolution":{"observed_at":"2026-08-06T20:28:40.261995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:39.973250Z","title":"Lost in the middle: How language mod- els use long contexts,","venue":null,"work_id":"81c4993e-0f57-4886-a707-3da6da55b422","year":2024},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.491769Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:3b2a6d4df336481e517e5d76a1868cbc01d040ca9a94ec155f282bb866eb2568","observation_id":"0fce3238-da73-4f58-9818-df52c0a03fdc","resolution":{"observed_at":"2026-08-06T20:28:40.072318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:39.755838Z","title":"Is attention interpretable?","venue":null,"work_id":"d09babc0-fee4-49de-8d73-1ed519753d09","year":2019},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.644890Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:fbf8071f900ada15f02097344046dbf8d22b74d399d94e7ca43916e4b404241a","observation_id":"ad71e619-2f55-4c73-9d09-0e444eb99e7a","resolution":{"observed_at":"2026-08-06T20:28:39.888480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05258","last_updated":"2025-04-07T12:04:28Z","snapshot_observed_at":"2026-08-03T16:01:59.392774Z","submitted_at":"2024-10-07T17:57:38Z","title":"Differential Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.05258","snapshot_observed_at":"2026-08-06T20:28:33.798137Z","title":"Differential transformer,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.798137Z"},"links":{"cited_paper":"/paper/2410.05258","citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:bd3ca6ecefeb212b650b6faeb72bd58e22249372ed39fd72534bdbd048d669e6","observation_id":"5905a8ce-cce7-483c-975b-37b382bca4a5","resolution":{"observed_at":"2026-08-06T20:28:33.798137Z","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":"2026-08-06T20:28:39.556695Z","title":"A wideband differential low-noise-amplifier with im3 harmonics and noise canceling,","venue":null,"work_id":"0229a9a0-c868-4b59-86c9-15852fe8a039","year":2015},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:33.932669Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:6e2943f64aa1f3b2a010e82d94eacfa6bb24ac14567831906b1026a1daeca5aa","observation_id":"95ec8a69-aefa-487f-9a52-afc843e93a3f","resolution":{"observed_at":"2026-08-06T20:28:39.630957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:39.337421Z","title":"A novel concept of smart headphones using active noise cancellation and speech recognition,","venue":null,"work_id":"b6533223-bbb0-45f9-9862-c870f1cde2b8","year":2015},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:34.071321Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:adbcb726c5416c22e67ec4ad6b3a22b43adb8163c502d184f3b1c301d444a04d","observation_id":"8f8ff9fe-067c-4818-828a-d8406bf632c9","resolution":{"observed_at":"2026-08-06T20:28:39.463913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:39.187884Z","title":"An exponen- tial moving average algorithm,","venue":null,"work_id":"4f74ba2f-b199-41fd-8357-dc9fd6b117f8","year":2012},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:34.229767Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:93247d539d37ae099e13813b50aa650cc0553241ea8b678099424fdbd4ccbddc","observation_id":"88d5ed6c-1eca-4d75-99e6-90979ac4d453","resolution":{"observed_at":"2026-08-06T20:28:39.255170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:38.873142Z","title":"data2vec: A general framework for self-supervised learning in speech, vision and language,","venue":null,"work_id":"2cf44951-103b-40ac-a722-2173ae315694","year":2022},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:34.372367Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:3f7509fac6377c0980a18d5fc7437db45c0459b48183181822b2a7a9ef7fdb9d","observation_id":"e512e3de-1fd6-4368-a31c-d84caba40da0","resolution":{"observed_at":"2026-08-06T20:28:39.002956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.08415","last_updated":"2023-06-06T01:53:32Z","snapshot_observed_at":"2026-07-06T05:01:27.910364Z","submitted_at":"2016-06-27T19:20:40Z","title":"Gaussian Error Linear Units (GELUs)","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.08415","snapshot_observed_at":"2026-08-06T20:28:34.505310Z","title":"Gaussian error linear units (gelus),","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:34.505310Z"},"links":{"cited_paper":"/paper/1606.08415","citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:0916dc69f4454a900da7967c8e9dd54f70ab1c998af92d5ffa71fe7414a310dd","observation_id":"9792aad9-7666-422a-88e0-2771d2e69316","resolution":{"observed_at":"2026-08-06T20:28:34.505310Z","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":"2026-08-06T20:28:38.638787Z","title":"Audio set: An ontology and human-labeled dataset for audio events,","venue":null,"work_id":"728f165f-5a14-4f93-80d1-6611e25616f8","year":2017},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:34.652537Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:3c58e19c0cb50bcc1a446df9350d96bac67904bd31dcacaa7452eb2a15599687","observation_id":"5925838f-fb38-40ff-ab2e-f9d984364f54","resolution":{"observed_at":"2026-08-06T20:28:38.770992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-06T20:28:34.828736Z","title":"Speech commands: A dataset for limited-vocabulary speech recognition,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:34.828736Z"},"links":{"cited_paper":"/paper/1804.03209","citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:e8e6f40383970aea02b583ea92f6a1c5bb3d39743542fc35f8c21ea6d34aff41","observation_id":"3c13d0e1-1e4c-4b56-8b90-b96052288b6d","resolution":{"observed_at":"2026-08-06T20:28:34.828736Z","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":"2026-08-06T20:28:38.317282Z","title":"Esc: Dataset for environmental sound classifica- tion,","venue":null,"work_id":"efdee3d8-74c5-4e26-89f2-616b5810c43a","year":2015},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:35.015561Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:13dd015d878fc969ffc106723b1f625bb69ec554e5a0c05dfb2b90b1a80f6e8e","observation_id":"0ea7cfa5-d2df-4229-8e76-ac37763d11eb","resolution":{"observed_at":"2026-08-06T20:28:38.503231Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:38.022563Z","title":"Ast: Audio spectrogram transformer,","venue":null,"work_id":"37b3e9fc-1dfe-4fa3-81ee-467fc7c2ce7a","year":2021},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:35.175188Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:cd13165b49c25d88d84dd95645cb7ebc7cdccc7a90e7e9eb7d6c7a2b223dd2fd","observation_id":"50fd7244-3494-4c5f-b670-bd941b5c9b5f","resolution":{"observed_at":"2026-08-06T20:28:38.159983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:37.655024Z","title":"Attention bottlenecks for multimodal fusion,","venue":null,"work_id":"9d7821bf-5932-4ab3-9b58-cd0b0fd58d62","year":2021},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:35.382149Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:cff403508b5d9815e2abcfcf79af9fcc72974586d5c8c87599f9b58ac27699d8","observation_id":"9d31c932-05e0-4a4b-a4eb-330476e18091","resolution":{"observed_at":"2026-08-06T20:28:37.850107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:37.298728Z","title":"Effi- cient training of audio transformers with patchout,","venue":null,"work_id":"04df61f5-ccb9-4f9a-b853-476f92d9a10c","year":2022},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:35.545464Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:c4ec9460d93f7f27cbb446ca3a6d45676ace3a1e2468702bf66b1ae8b71cc123","observation_id":"511bcd7e-44eb-4d14-8f1b-9b4958906c96","resolution":{"observed_at":"2026-08-06T20:28:37.484722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:36.993047Z","title":"Conformer-based self-supervised learning for non- speech audio tasks,","venue":null,"work_id":"cb0946c9-6016-485d-a318-698204838318","year":2022},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:35.695590Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:50ef0fd21e2b4faf3d51f6634fed2570123a50ad609eb2ee5837ceb1827fd70f","observation_id":"20bae886-755b-4177-b485-246e717883e9","resolution":{"observed_at":"2026-08-06T20:28:37.127599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T20:28:36.648684Z","title":"Adam: A method for stochastic opti- mization,","venue":null,"work_id":"ed64a839-2b70-404f-9580-939dbb8b5604","year":2015},"citing_paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:28:35.807111Z"},"links":{"citing_paper":"/paper/2507.02666"},"observation_digest":"sha256:e98162258e2e1228cea2470f509f2bd5ce038b0737c9c4827ddbfac5059440d1","observation_id":"b9464ad4-038e-4b8f-b1a1-82856d3e764e","resolution":{"observed_at":"2026-08-06T20:28:36.766015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.02666","last_updated":"2025-07-03T14:29:43Z","latest_version":1,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-07T04:56:47.698276Z","submitted_at":"2025-07-03T14:29:43Z","title":"ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":5,"verified_exact":1,"verified_fuzzy":26},"total_outbound_references":33},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2507.02666."}