{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MYAH3ZAGKXJJWSYLGOVZBRI6BE","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":"16f64961636ca4e18b59fe7f4921ee26808cfc9e57b9c1e9d7d8d77340d98727","cross_cats_sorted":["cs.AI","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2024-11-21T00:29:58Z","title_canon_sha256":"9a1a9ec27fb0cfb3664c9d0fe88aa061f50579cbd7d18e15902081750d2c80c4"},"schema_version":"1.0","source":{"id":"2411.13766","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.13766","created_at":"2026-07-05T11:35:52Z"},{"alias_kind":"arxiv_version","alias_value":"2411.13766v4","created_at":"2026-07-05T11:35:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.13766","created_at":"2026-07-05T11:35:52Z"},{"alias_kind":"pith_short_12","alias_value":"MYAH3ZAGKXJJ","created_at":"2026-07-05T11:35:52Z"},{"alias_kind":"pith_short_16","alias_value":"MYAH3ZAGKXJJWSYL","created_at":"2026-07-05T11:35:52Z"},{"alias_kind":"pith_short_8","alias_value":"MYAH3ZAG","created_at":"2026-07-05T11:35:52Z"}],"graph_snapshots":[{"event_id":"sha256:ad341a612669c4e6156e0051fbf3696f713a66e7adadbd972c851b2f6b0c336b","target":"graph","created_at":"2026-07-05T11:35:52Z","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/2411.13766/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The combination of Large Language Models (LLM) and Automatic Speech Recognition (ASR), when deployed on edge devices (called edge ASR-LLM), can serve as a powerful personalized assistant to enable audio-based interaction for users. Compared to text-based interaction, edge ASR-LLM allows accessible and natural audio interactions. Unfortunately, existing ASR-LLM models are mainly trained in high-performance computing environments and produce substantial model weights, making them difficult to deploy on edge devices. More importantly, to better serve users' personalized needs, the ASR-LLM must be","authors_text":"Chenhui Xu, Dancheng Liu, Gelei Xu, Jinjun Xiong, Ruiyang Qin, Shaocong Wang, X. Sharon Hu, Yiyu Shi, Yuting Hu, Zheyu Yan","cross_cats":["cs.AI","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2024-11-21T00:29:58Z","title":"Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.13766","kind":"arxiv","version":4},"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":"sha256:7163abc9da18ff7f7c5b67f3c431534c4249258fc2a55aefb06b1e6edb0f99ef","target":"record","created_at":"2026-07-05T11:35:52Z","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":"16f64961636ca4e18b59fe7f4921ee26808cfc9e57b9c1e9d7d8d77340d98727","cross_cats_sorted":["cs.AI","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2024-11-21T00:29:58Z","title_canon_sha256":"9a1a9ec27fb0cfb3664c9d0fe88aa061f50579cbd7d18e15902081750d2c80c4"},"schema_version":"1.0","source":{"id":"2411.13766","kind":"arxiv","version":4}},"canonical_sha256":"66007de40655d29b4b0b33ab90c51e0919d325e5f98341efa774178b8c33188c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66007de40655d29b4b0b33ab90c51e0919d325e5f98341efa774178b8c33188c","first_computed_at":"2026-07-05T11:35:52.237108Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:35:52.237108Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QknZ4az1QkelR9GZK6obgYQVAqSc8RRQ5RrmgOp45tjpyECcwY75VJ5NrCXeSBAWetWlTTfCrMh2HXGfasF+Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T11:35:52.237687Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.13766","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7163abc9da18ff7f7c5b67f3c431534c4249258fc2a55aefb06b1e6edb0f99ef","sha256:ad341a612669c4e6156e0051fbf3696f713a66e7adadbd972c851b2f6b0c336b"],"state_sha256":"0dc4dcb014927ae14e649a41eea6404eb7bf8162e407f24a680c939980c10acb"}