{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:YNOWIVCL2K2YBXFH76G5ZFUU7H","short_pith_number":"pith:YNOWIVCL","schema_version":"1.0","canonical_sha256":"c35d64544bd2b580dca7ff8ddc9694f9f575a87e84050c12499734242eef869b","source":{"kind":"arxiv","id":"2606.00507","version":1},"attestation_state":"computed","paper":{"title":"LaSR: Context-Aware Speech Recognition via Latent Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Heyang Liu, Jiayi Huang, Qunshan Gu, Ronghua Wu, Wenyang Xiao, Yanfeng Wang, Yu Wang, Ziyang Cheng","submitted_at":"2026-05-30T03:44:12Z","abstract_excerpt":"Recent advances in Speech Large Language Models (Speech LLMs) have significantly enhanced spoken language understanding and reasoning. However, their contextual awareness is limited, struggling to perform speech recognition that effectively reflects the speaker's intent and topical context. In this paper, we propose LaSR (Latent Speech Reasoning), a novel training paradigm featuring a context-aware reasoning trajectory that leverages the latent reasoning process. Instead of generating explicit intermediate tokens, LaSR aligns chain-of-thought (CoT) supervision around the acoustic feature regio"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.00507","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-30T03:44:12Z","cross_cats_sorted":[],"title_canon_sha256":"e2b10aec31d514b19400fdc324ae03d3016ced77dd94e0218046dd7c35502140","abstract_canon_sha256":"a150db13b30f39030f24c842217502195520d87579d861c892743192bd75d3e6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T01:03:56.796793Z","signature_b64":"fbsO5CDNbOftMz21FkTdyhsSAvBQjZNx7e0S8QBipJTPdNI+0RMHtPCzhAJUpTNjCn5THRtBtop0kM1/WSD3Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c35d64544bd2b580dca7ff8ddc9694f9f575a87e84050c12499734242eef869b","last_reissued_at":"2026-06-02T01:03:56.796404Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T01:03:56.796404Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LaSR: Context-Aware Speech Recognition via Latent Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Heyang Liu, Jiayi Huang, Qunshan Gu, Ronghua Wu, Wenyang Xiao, Yanfeng Wang, Yu Wang, Ziyang Cheng","submitted_at":"2026-05-30T03:44:12Z","abstract_excerpt":"Recent advances in Speech Large Language Models (Speech LLMs) have significantly enhanced spoken language understanding and reasoning. However, their contextual awareness is limited, struggling to perform speech recognition that effectively reflects the speaker's intent and topical context. In this paper, we propose LaSR (Latent Speech Reasoning), a novel training paradigm featuring a context-aware reasoning trajectory that leverages the latent reasoning process. Instead of generating explicit intermediate tokens, LaSR aligns chain-of-thought (CoT) supervision around the acoustic feature regio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.00507","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.00507/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.00507","created_at":"2026-06-02T01:03:56.796455+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.00507v1","created_at":"2026-06-02T01:03:56.796455+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.00507","created_at":"2026-06-02T01:03:56.796455+00:00"},{"alias_kind":"pith_short_12","alias_value":"YNOWIVCL2K2Y","created_at":"2026-06-02T01:03:56.796455+00:00"},{"alias_kind":"pith_short_16","alias_value":"YNOWIVCL2K2YBXFH","created_at":"2026-06-02T01:03:56.796455+00:00"},{"alias_kind":"pith_short_8","alias_value":"YNOWIVCL","created_at":"2026-06-02T01:03:56.796455+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H","json":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H.json","graph_json":"https://pith.science/api/pith-number/YNOWIVCL2K2YBXFH76G5ZFUU7H/graph.json","events_json":"https://pith.science/api/pith-number/YNOWIVCL2K2YBXFH76G5ZFUU7H/events.json","paper":"https://pith.science/paper/YNOWIVCL"},"agent_actions":{"view_html":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H","download_json":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H.json","view_paper":"https://pith.science/paper/YNOWIVCL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.00507&json=true","fetch_graph":"https://pith.science/api/pith-number/YNOWIVCL2K2YBXFH76G5ZFUU7H/graph.json","fetch_events":"https://pith.science/api/pith-number/YNOWIVCL2K2YBXFH76G5ZFUU7H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H/action/storage_attestation","attest_author":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H/action/author_attestation","sign_citation":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H/action/citation_signature","submit_replication":"https://pith.science/pith/YNOWIVCL2K2YBXFH76G5ZFUU7H/action/replication_record"}},"created_at":"2026-06-02T01:03:56.796455+00:00","updated_at":"2026-06-02T01:03:56.796455+00:00"}