{"as_of":"2026-08-11T20:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:175c9b2f76e768a9e13ae1a612c54d5a7864f734885b4a3b71aa5c56b7c65389","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T04:32:31.857707Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2608.06409/citation-record","integrity":"/paper/2608.06409/integrity","json":"/paper/2608.06409/citation-record.json","paper":"/paper/2608.06409"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.20215","last_updated":"2025-03-26T04:17:55Z","snapshot_observed_at":"2026-08-06T08:46:20.194739Z","submitted_at":"2025-03-26T04:17:55Z","title":"Qwen2.5-Omni Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20215","snapshot_observed_at":"2026-08-10T04:32:31.744530Z","title":"Qwen2.5-omni technical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.744530Z"},"links":{"cited_paper":"/paper/2503.20215","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:3f8b9cbf99ff10bf95469b212a925e88215d36218196c8532c0452b549504be8","observation_id":"12fc2f26-e210-4872-8367-3d12a1a249b8","resolution":{"observed_at":"2026-08-10T04:32:31.744530Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10759","last_updated":"2024-07-15T14:38:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T14:38:09Z","title":"Qwen2-Audio Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10759","snapshot_observed_at":"2026-08-10T04:32:31.748709Z","title":"Qwen2-audio technical report,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.748709Z"},"links":{"cited_paper":"/paper/2407.10759","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:d90ca9c0a9e2944a093df62d573cb2f5fe189a3aee83206b1a751d2ef62b69f0","observation_id":"6b1d5867-a5d2-4b12-907a-4be96bf25341","resolution":{"observed_at":"2026-08-10T04:32:31.748709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.08128","last_updated":"2025-07-28T22:53:43Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-10T19:40:21Z","title":"Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.08128","snapshot_observed_at":"2026-08-10T04:32:31.751914Z","title":"Audio flamingo 3: Advancing audio intelligence with fully open large audio language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.751914Z"},"links":{"cited_paper":"/paper/2507.08128","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:ea08b6a022b6804df64a98c626a342ed4e831d4aa5bf754374fc6e86ae8b4093","observation_id":"7df22cbd-5337-4217-b9fd-2d77c200377e","resolution":{"observed_at":"2026-08-10T04:32:31.751914Z","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":"2026-08-10T04:32:32.348669Z","title":"Kimi-audio technical report,","venue":null,"work_id":"08235608-395a-49e6-92d9-73c14ccd5b2c","year":2025},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.755774Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:45c19d36fd6f13d6a126256ecf3a55afdfa671884bb98e490d20002770c08130","observation_id":"7169cc16-c308-4225-8642-e29ac828e1da","resolution":{"observed_at":"2026-08-10T04:32:32.351418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08905","last_updated":"2024-12-12T03:37:41Z","snapshot_observed_at":"2026-08-05T04:04:21.846023Z","submitted_at":"2024-12-12T03:37:41Z","title":"Phi-4 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08905","snapshot_observed_at":"2026-08-10T04:32:31.758858Z","title":"Phi- 4 technical report,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.758858Z"},"links":{"cited_paper":"/paper/2412.08905","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:35a6f9845228593bcf572748280f580d254b9677b2210937451c8ac3f0cb78aa","observation_id":"1f549bc2-f8db-46eb-9657-e954e9be14af","resolution":{"observed_at":"2026-08-10T04:32:31.758858Z","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":"2026-08-10T04:32:32.338965Z","title":"Dynamic-superb: Towards a dynamic, collaborative, and comprehensive instruction-tuning bench- mark for speech,","venue":null,"work_id":"0665708d-b70f-431a-af13-b80cc8f2b04e","year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.762009Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:b115e268c7e3b48d82e7d0a5ceefda4cc4e2a83bdafc82331f47ad6beceb79e0","observation_id":"e5e3798a-e601-4e98-b73d-f23e6beae2bc","resolution":{"observed_at":"2026-08-10T04:32:32.342391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:31.764890Z","title":"Air-bench: Benchmarking large audio-language models via generative comprehension,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.764890Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:d6686d14bd403e2786a802341e78bc02fd84d0f64db87a249ef1cad36e35d116","observation_id":"5a74baf5-dfff-4e1d-ba59-47745e2b5ba9","resolution":{"observed_at":"2026-08-10T04:32:31.764890Z","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":"2026-08-10T04:32:32.324127Z","title":"Sd-eval: A benchmark dataset for spoken dialogue under- standing beyond words,","venue":null,"work_id":"de4f6fde-c97c-46f6-bb43-db00d3888680","year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.767679Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:0a9e47d7ebccd7a8151a469d202bc9406db04f2f40bc38484afe53154a53e3c8","observation_id":"514276ec-cd9f-4def-8c4f-e1cc9e407b2b","resolution":{"observed_at":"2026-08-10T04:32:32.327593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:32.315158Z","title":"V ocal communication of emotion: A review of research paradigms,","venue":null,"work_id":"bcde92bc-7a84-4170-8dc0-f958727236cb","year":2003},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.770216Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:327aa772d1c8a78bd98b4344c55efc2749a88e81d2f837672acb974907458e87","observation_id":"73518e17-ad29-4a05-a8ed-85e3b0495df2","resolution":{"observed_at":"2026-08-10T04:32:32.318384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:32.304093Z","title":"Communication of emotions in vocal expression and music performance: Different channels, same code?","venue":null,"work_id":"378ab733-1947-40f2-a224-ba07f59eb082","year":2003},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.772730Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:da894f965f7d8aaf05b7329960226e710a8e57f3e4e2995e6360d6970883d192","observation_id":"84c1c3fa-3f22-4829-9065-125e7e961368","resolution":{"observed_at":"2026-08-10T04:32:32.308892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:31.775354Z","title":"Crema-d: Crowd-sourced emotional multimodal actors dataset,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.775354Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:be503e4d3e29c5e48722fa87288b4c157f0c54f4bb8c7f9cea2af17b5fc46c44","observation_id":"0b853dc7-4226-41e7-9c07-496e62ae3e72","resolution":{"observed_at":"2026-08-10T04:32:31.775354Z","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":"2026-08-10T04:32:32.280916Z","title":"Calibrate before use: Improving few-shot performance of language models,","venue":null,"work_id":"fe1aaf54-41b0-4362-bfa1-5df610cbb10d","year":2021},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.778308Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:2d2a9c1b1ce75814de942dd9f832c83ad624c0761664e4df7612184d1cb6615a","observation_id":"21baf8da-79c4-415f-bf8f-335cb0217c49","resolution":{"observed_at":"2026-08-10T04:32:32.284663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17249","last_updated":"2024-12-01T01:36:50Z","snapshot_observed_at":"2026-07-06T16:25:29.858870Z","submitted_at":"2023-09-29T13:55:45Z","title":"Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17249","snapshot_observed_at":"2026-08-10T04:32:31.781328Z","title":"Batch calibration: Rethinking calibration for in-context learning and prompt engineering,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.781328Z"},"links":{"cited_paper":"/paper/2309.17249","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:b25ec4a4c5db4d607284f253ad64f5b5f9424d2757eb2b825ef4f3592fb0a726","observation_id":"ea5c18ea-ad1b-4da2-b542-f9db439a562e","resolution":{"observed_at":"2026-08-10T04:32:31.781328Z","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":"2026-08-10T04:32:31.784638Z","title":"Speechgpt: Empowering large language models with intrinsic cross- modal conversational abilities,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.784638Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:806aec840004210879fdc6f29e347b0a6b7fec67df2865f1a0aea1b715bfa88e","observation_id":"7c06e0b6-47a1-4b6d-907c-8f2e6f0f9fcd","resolution":{"observed_at":"2026-08-10T04:32:31.784638Z","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":"2026-08-10T04:32:32.265873Z","title":"Salmonn: Towards generic hearing abilities for large language models,","venue":null,"work_id":"2d493811-b04b-4292-9eea-7a26553de191","year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.787548Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:75b3b22e8993c54f30dcea83f34b35762026c492f1c7181c24fa36492f8134c8","observation_id":"b4495293-cf5d-4097-b97a-12ffc1a69720","resolution":{"observed_at":"2026-08-10T04:32:32.268581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01831","last_updated":"2024-05-28T05:44:53Z","snapshot_observed_at":"2026-08-07T19:26:44.980429Z","submitted_at":"2024-02-02T18:58:34Z","title":"Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01831","snapshot_observed_at":"2026-08-10T04:32:31.790153Z","title":"Audio flamingo: A novel audio language model with few-shot learning and dialogue abilities,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.790153Z"},"links":{"cited_paper":"/paper/2402.01831","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:610978830a398e9ab6f1d52475bbfeb4cbb36ac29aa632ff60a8902357e300a2","observation_id":"975be820-add6-4905-8c1e-0de9bccd650b","resolution":{"observed_at":"2026-08-10T04:32:31.790153Z","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":"2026-08-10T04:32:32.256794Z","title":"Do audio LLMs really LISTEN, or just transcribe? measuring lexical vs. acoustic emotion cues reliance,","venue":null,"work_id":"d2ec110b-65ae-408f-9907-45ed99948cef","year":2026},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.793462Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:80bd449243851845931d4d566c20f2c148ccd0b06575408e7ec4a588c5fdc26f","observation_id":"3eb2572c-a031-49a5-9ce0-ca827b501a8e","resolution":{"observed_at":"2026-08-10T04:32:32.260228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03882","last_updated":"2024-02-22T01:40:35Z","snapshot_observed_at":"2026-08-06T19:10:47.693909Z","submitted_at":"2023-09-07T17:44:56Z","title":"Large Language Models Are Not Robust Multiple Choice Selectors","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.03882","snapshot_observed_at":"2026-08-10T04:32:31.796280Z","title":"Large language models are not robust multiple choice selectors,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.796280Z"},"links":{"cited_paper":"/paper/2309.03882","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:3c081d9f6cc528849b561cf206ce860e8fe15f4436e93f8db3c87103cffca456","observation_id":"a342f4ec-b2ba-4a16-9a7a-2ec0c823efe3","resolution":{"observed_at":"2026-08-10T04:32:31.796280Z","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":"2026-08-10T04:32:32.246951Z","title":"Answer-level calibration for free-form multiple choice ques- tion answering,","venue":null,"work_id":"7715b439-f349-4071-8ceb-4b0f40e058ea","year":2022},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.799510Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:aafcf2c322830103f0048de06c1888db71ad19f4d4a666feb2dbc016b8f7ecb2","observation_id":"2f238438-bd9e-441c-a9de-d0807bd603b7","resolution":{"observed_at":"2026-08-10T04:32:32.250869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:31.803074Z","title":"Hubert: Self-supervised speech representation learning by masked prediction of hidden units,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.803074Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:60deb4e4d1c7d40d04528a44b063358b33fb94c88c09d109e49fdcffdb8505ca","observation_id":"55b95ac9-c208-44b8-980f-53e4562a4e8e","resolution":{"observed_at":"2026-08-10T04:32:31.803074Z","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":"2026-08-10T04:32:31.806129Z","title":"Wavlm: Large-scale self-supervised pre- training for full stack speech processing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.806129Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:8a9c3fda857f80f7d74bda166c15e7bf6020c72e5a3c70bbcca76c1b6e6e3a03","observation_id":"2d5956e8-bd0a-40fe-9de2-4cace1eb436b","resolution":{"observed_at":"2026-08-10T04:32:31.806129Z","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":"2026-08-10T04:32:31.809159Z","title":"Robust speech recognition via large-scale weak supervi- sion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.809159Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:e1fe49d4f82c52494061f35ff657d875cf8f204274f6318f2ad8efcd05df9fd2","observation_id":"caa98c24-0039-4434-ac89-9f289bd86581","resolution":{"observed_at":"2026-08-10T04:32:31.809159Z","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":"2026-08-10T04:32:31.812197Z","title":"Layer-wise analysis of a self-supervised speech representation model,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.812197Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:18520f7f2872bc0edde25fc16343bb36752528bc7470ac84451e6f8f8c812764","observation_id":"15dd4bdf-9119-43c7-bcef-508061614cdd","resolution":{"observed_at":"2026-08-10T04:32:31.812197Z","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":"2026-08-10T04:32:32.216284Z","title":"Probing phoneme, language and speaker information in unsupervised speech representations,","venue":null,"work_id":"93c288c7-58c0-40f5-8e05-16d7c6e520b1","year":2022},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.815341Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:c72c314c9698f6d5dd3b9c678df1538c5066516cb8744bf202bcb80cd58d4dc5","observation_id":"d95b1587-b325-4ae9-8fe7-80e61dfb5db2","resolution":{"observed_at":"2026-08-10T04:32:32.219835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:32.206835Z","title":"Dawn of the transformer era in speech emotion recognition: Closing the valence gap,","venue":null,"work_id":"630f2a94-2d39-42be-aea7-8894d0178ae4","year":2023},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.818385Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:74e4116f9538d7729158c48973c6973cda5f855d143ea9f58bf5b64e8f42362e","observation_id":"8a24cd67-ef46-40c3-91c3-e4cf0f41e746","resolution":{"observed_at":"2026-08-10T04:32:32.210353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:31.821264Z","title":"emotion2vec: Self-supervised pre-training for speech emotion repre- sentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.821264Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:816895cc3b05d96da7b7e5b7e45f9d18431a8decc95fe8a0f8020531692c9070","observation_id":"d941a1d7-0c41-496d-95a6-c3be79a69a4f","resolution":{"observed_at":"2026-08-10T04:32:31.821264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.05140","last_updated":"2025-08-24T16:16:18Z","snapshot_observed_at":"2026-08-09T05:46:01.132153Z","submitted_at":"2025-06-05T15:22:47Z","title":"AudioLens: A Closer Look at Auditory Attribute Perception of Large Audio-Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.05140","snapshot_observed_at":"2026-08-10T04:32:31.824223Z","title":"AudioLens: A closer look at auditory attribute perception of large audio-language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.824223Z"},"links":{"cited_paper":"/paper/2506.05140","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:bc2155b4a6d139aa5dc9ab7ae5fffc2416524551a9a27851f2e624120019291f","observation_id":"9b8cb20c-c684-4561-851e-9dbd9768238f","resolution":{"observed_at":"2026-08-10T04:32:31.824223Z","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":"2026-08-10T04:32:31.827506Z","title":"Probing classifiers: Promises, shortcomings, and ad- vances,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.827506Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:bec8f972381268a235bb8f02005c7290418059adec5c87a34c8734180a632f49","observation_id":"cdcc73b5-582e-4ab3-84d1-176c007af2dc","resolution":{"observed_at":"2026-08-10T04:32:31.827506Z","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":"2026-08-10T04:32:32.186800Z","title":"Interpreting GPT: The logit lens,","venue":null,"work_id":"1b0e54f4-539c-4108-96d2-27e397d9b167","year":2020},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.830052Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:50f075648d0c76505a779fe363e03a6e15ade937132eafb963512059315770d3","observation_id":"7e1e1750-5569-426a-9efc-2dff05f7ae46","resolution":{"observed_at":"2026-08-10T04:32:32.189362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08112","last_updated":"2025-11-11T01:13:28Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-03-14T17:47:09Z","title":"Eliciting Latent Predictions from Transformers with the Tuned Lens","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08112","snapshot_observed_at":"2026-08-10T04:32:31.832716Z","title":"Eliciting latent predictions from trans- formers with the tuned lens,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.832716Z"},"links":{"cited_paper":"/paper/2303.08112","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:03670f06bf33b61ff8f83961fb1a8ab241f4710a42d62392947e491ae3232d4b","observation_id":"0ddd82d8-1421-4acf-a6f1-958a9fc9eb74","resolution":{"observed_at":"2026-08-10T04:32:31.832716Z","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":"2026-08-10T04:32:32.177596Z","title":"Investigating gender bias in language models using causal mediation analysis,","venue":null,"work_id":"49c0df9c-cc76-4204-b503-ee08d3c4a57a","year":2020},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.835497Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:92de79004361be8e3bb454e9808dc62a4b9f9a38c35b7486a15781cc3b1dd073","observation_id":"1cd0d5de-6a37-4cb8-b987-f20dd1ccde1b","resolution":{"observed_at":"2026-08-10T04:32:32.180872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:32.167759Z","title":"Causal abstractions of neural networks,","venue":null,"work_id":"d65c49e9-bb66-4578-bb6e-314c55ab1820","year":2021},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.838302Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:2acdc9a2329af5a61fa9767de31acb6c79b58f4e1568d80bf4b565c852101e6e","observation_id":"a572b513-5b0e-49d3-a1ab-73c952795bee","resolution":{"observed_at":"2026-08-10T04:32:32.171051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:31.841090Z","title":"Locating and editing factual associations in gpt,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.841090Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:553abe8061e9b8681452eb2a95f76f8bc116222b36d9ad907c6f3e74bc65aaf9","observation_id":"cf029d59-5115-49fa-9785-ff579905f8aa","resolution":{"observed_at":"2026-08-10T04:32:31.841090Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17030","last_updated":"2023-12-06T14:28:46Z","snapshot_observed_at":"2026-08-10T22:16:16.885194Z","submitted_at":"2023-11-28T18:32:19Z","title":"Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17030","snapshot_observed_at":"2026-08-10T04:32:31.843709Z","title":"Is this the subspace you are looking for? an interpretability illusion for subspace activation patching,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.843709Z"},"links":{"cited_paper":"/paper/2311.17030","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:1f57978e4aedb0579ed7187a1beefe745ee60ddeeda298a6e292da750fab65c7","observation_id":"54b8722f-1044-4f42-97ec-c41e226f8953","resolution":{"observed_at":"2026-08-10T04:32:31.843709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.23782","last_updated":"2026-06-01T03:35:05Z","snapshot_observed_at":"2026-08-04T14:43:07.447205Z","submitted_at":"2025-09-28T09:57:24Z","title":"Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.23782","snapshot_observed_at":"2026-08-10T04:32:31.846587Z","title":"Bridging the knowledge-prediction gap in LLMs on multiple-choice questions,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.846587Z"},"links":{"cited_paper":"/paper/2509.23782","citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:1a9dace2d354baef5a985f54f62d31c71dcbda528e5a856d0c5f90ad2027cda5","observation_id":"a16442fd-35b7-4eb5-b923-cc08be8f495a","resolution":{"observed_at":"2026-08-10T04:32:31.846587Z","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":"2602.22253","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:32.026336Z","title":"AR&D: A framework for retrieving and describing concepts for interpreting AudioLLMs,","venue":null,"work_id":"8aeca3c7-dadf-4217-a421-78f3c7af3803","year":2026},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.849918Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:5ce4a0fddc4fe5a6a6a569add728c10bf5c8808fb0889bef4d78235edbd8ffa6","observation_id":"47eb4545-247f-4fa5-8bda-220483bfde1a","resolution":{"observed_at":"2026-08-10T04:32:32.031362Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:32.151849Z","title":"Who wins the conflict? mechanistic interpretability of text bias in audio LLMs,","venue":null,"work_id":"8861f579-2636-459b-9d5f-480a4632b7cc","year":2026},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.852436Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:84e32612f37929b2e62d0a0c752df6717dee4ad54b5052947efa879b51842be4","observation_id":"02154628-7b4f-461a-b37b-39cd7ad01534","resolution":{"observed_at":"2026-08-10T04:32:32.154974Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:32:32.140501Z","title":"VESUS: A crowd-annotated database to study emotion production and perception in spoken English,","venue":null,"work_id":"8447767d-6cb4-4b00-b842-867fa017b57d","year":2019},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.855121Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:1abb66693c14c65ae71ec3c955d7802dd2a86be48b0b358d401a757560364931","observation_id":"66530ff9-482e-4856-a6a1-cd81a27d2b6a","resolution":{"observed_at":"2026-08-10T04:32:32.144647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"0981.0000","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:32:31.958380Z","title":"A theory of usable information under computational constraints,","venue":null,"work_id":"509c3fb5-b6c0-46c5-8c3b-8e43cca58699","year":2020},"citing_paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T04:32:31.857707Z"},"links":{"citing_paper":"/paper/2608.06409"},"observation_digest":"sha256:0106af39625ce1ab7f9ca3afbf0d604bc9221a681c085504ca6407dbec306103","observation_id":"f28e80ba-7aed-4275-b341-81ebfbb19afb","resolution":{"observed_at":"2026-08-10T04:32:31.964757Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.06409","last_updated":"2026-08-03T17:34:33Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T20:09:44.224248Z","submitted_at":"2026-08-03T17:34:33Z","title":"Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":1,"verified_fuzzy":16},"total_outbound_references":39},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2608.06409."}