{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:NHZ5L3ZXBLXVC6NB6OI3PKTSGV","short_pith_number":"pith:NHZ5L3ZX","schema_version":"1.0","canonical_sha256":"69f3d5ef370aef5179a1f391b7aa72354967914a82d71f7993bf662c796110bb","source":{"kind":"arxiv","id":"2607.28175","version":1},"attestation_state":"computed","paper":{"title":"AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Binghao Qiang, Jiaying Chi, Kai Yu, Xie Chen, Yanqiao Zhu, Zixuan Jiang","submitted_at":"2026-07-30T13:12:25Z","abstract_excerpt":"Automatic speech recognition (ASR) has achieved substantial gains in transcription accuracy, yet verbatim transcription does not necessarily produce readily usable text. It retains fillers, repetitions, false starts, and self-corrections that increase reading effort, obscure the speaker's final intent, and propagate unresolved or abandoned content to downstream tasks. Existing spoken-to-written methods process completed audio or transcripts but cannot revise emitted text when later speech changes how preceding content should be interpreted. We therefore formulate Agentic Speech Recognition (Ag"},"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":"2607.28175","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-30T13:12:25Z","cross_cats_sorted":[],"title_canon_sha256":"a5c8cedd826a16ff289a3a37262a05f1922986288f69a99dbc02e4004cb64b61","abstract_canon_sha256":"188208a88c216a5e2cc7f1a19a704e8489013d44f11d1468448a080bcace8c13"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"69f3d5ef370aef5179a1f391b7aa72354967914a82d71f7993bf662c796110bb","last_reissued_at":"2026-07-31T01:36:16.325641Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:36:16.325641Z"},"graph_snapshot":{"paper":{"title":"AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Binghao Qiang, Jiaying Chi, Kai Yu, Xie Chen, Yanqiao Zhu, Zixuan Jiang","submitted_at":"2026-07-30T13:12:25Z","abstract_excerpt":"Automatic speech recognition (ASR) has achieved substantial gains in transcription accuracy, yet verbatim transcription does not necessarily produce readily usable text. It retains fillers, repetitions, false starts, and self-corrections that increase reading effort, obscure the speaker's final intent, and propagate unresolved or abandoned content to downstream tasks. Existing spoken-to-written methods process completed audio or transcripts but cannot revise emitted text when later speech changes how preceding content should be interpreted. We therefore formulate Agentic Speech Recognition (Ag"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28175","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/2607.28175/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":"2607.28175","created_at":"2026-07-31T01:36:16.328864+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.28175v1","created_at":"2026-07-31T01:36:16.328864+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28175","created_at":"2026-07-31T01:36:16.328864+00:00"},{"alias_kind":"pith_short_12","alias_value":"NHZ5L3ZXBLXV","created_at":"2026-07-31T01:36:16.328864+00:00"},{"alias_kind":"pith_short_16","alias_value":"NHZ5L3ZXBLXVC6NB","created_at":"2026-07-31T01:36:16.328864+00:00"},{"alias_kind":"pith_short_8","alias_value":"NHZ5L3ZX","created_at":"2026-07-31T01:36:16.328864+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/NHZ5L3ZXBLXVC6NB6OI3PKTSGV","json":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV.json","graph_json":"https://pith.science/api/pith-number/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/graph.json","events_json":"https://pith.science/api/pith-number/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/events.json","paper":"https://pith.science/paper/NHZ5L3ZX"},"agent_actions":{"view_html":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV","download_json":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV.json","view_paper":"https://pith.science/paper/NHZ5L3ZX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.28175&json=true","fetch_graph":"https://pith.science/api/pith-number/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/graph.json","fetch_events":"https://pith.science/api/pith-number/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/action/storage_attestation","attest_author":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/action/author_attestation","sign_citation":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/action/citation_signature","submit_replication":"https://pith.science/pith/NHZ5L3ZXBLXVC6NB6OI3PKTSGV/action/replication_record"}},"created_at":"2026-07-31T01:36:16.328864+00:00","updated_at":"2026-07-31T01:36:16.328864+00:00"}