{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GYM6TA7DVH6RDTGAXHNZH74IT7","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"abb0c4b873cfe904947b88849fe0e21f24777cb7185399310d470a6c076466b2","cross_cats_sorted":["eess.AS","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-28T08:29:00Z","title_canon_sha256":"0fee26feb8e0ce4b9a9e9a468f4feffde7a166a009e874f1014b0be1519a2e1a"},"schema_version":"1.0","source":{"id":"2306.16007","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.16007","created_at":"2026-07-05T06:25:47Z"},{"alias_kind":"arxiv_version","alias_value":"2306.16007v1","created_at":"2026-07-05T06:25:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.16007","created_at":"2026-07-05T06:25:47Z"},{"alias_kind":"pith_short_12","alias_value":"GYM6TA7DVH6R","created_at":"2026-07-05T06:25:47Z"},{"alias_kind":"pith_short_16","alias_value":"GYM6TA7DVH6RDTGA","created_at":"2026-07-05T06:25:47Z"},{"alias_kind":"pith_short_8","alias_value":"GYM6TA7D","created_at":"2026-07-05T06:25:47Z"}],"graph_snapshots":[{"event_id":"sha256:de6d81b92bd72a9144df49c26b2dc696fb012d8ef4ae0c055321f3607e54e364","target":"graph","created_at":"2026-07-05T06:25:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2306.16007/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The integration of Language Models (LMs) has proven to be an effective way to address domain shifts in speech recognition. However, these approaches usually require a significant amount of target domain text data for the training of LMs. Different from these methods, in this work, with only a domain-specific text prompt, we propose two zero-shot ASR domain adaptation methods using LLaMA, a 7-billion-parameter large language model (LLM). LLM is used in two ways: 1) second-pass rescoring: reranking N-best hypotheses of a given ASR system with LLaMA; 2) deep LLM-fusion: incorporating LLM into the","authors_text":"Jinyu Li, Shujie Liu, Yuang Li, Yu Wu","cross_cats":["eess.AS","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-28T08:29:00Z","title":"Prompting Large Language Models for Zero-Shot Domain Adaptation in Speech Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.16007","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:3ac82bd43bac31e4f1f0275623c694d1cc356090e2453f8e97eff760fe8f5f3c","target":"record","created_at":"2026-07-05T06:25:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"abb0c4b873cfe904947b88849fe0e21f24777cb7185399310d470a6c076466b2","cross_cats_sorted":["eess.AS","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-28T08:29:00Z","title_canon_sha256":"0fee26feb8e0ce4b9a9e9a468f4feffde7a166a009e874f1014b0be1519a2e1a"},"schema_version":"1.0","source":{"id":"2306.16007","kind":"arxiv","version":1}},"canonical_sha256":"3619e983e3a9fd11ccc0b9db93ff889ff808638dc6813ecedca8e4b88775e579","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3619e983e3a9fd11ccc0b9db93ff889ff808638dc6813ecedca8e4b88775e579","first_computed_at":"2026-07-05T06:25:47.608725Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:25:47.608725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"i1CtyIbLkfyEKlb+6LJnI2QEcWIU0cBikUl4MM3wbwKKfUUj8BsYzHPQ965z4PRnPoTj8rpD9mLzUc/6zs9ICQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:25:47.609209Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.16007","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3ac82bd43bac31e4f1f0275623c694d1cc356090e2453f8e97eff760fe8f5f3c","sha256:de6d81b92bd72a9144df49c26b2dc696fb012d8ef4ae0c055321f3607e54e364"],"state_sha256":"05da9785798cb12210543be7953c380c8b3655d03672fc596e546179498b5b1c"}