{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:M33TPOSLFJT5SAZ3EW4Q6YSECB","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":"8d79ffffcb935edca2269d477721f46b1f89982375ca985d8bd0c7308af3addc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-05T04:06:56Z","title_canon_sha256":"e4557d1a608b9b8bb014c4af6cd5187d40f0a8e51b41b86009e09b571e6d5366"},"schema_version":"1.0","source":{"id":"2410.04027","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.04027","created_at":"2026-07-05T09:16:27Z"},{"alias_kind":"arxiv_version","alias_value":"2410.04027v1","created_at":"2026-07-05T09:16:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.04027","created_at":"2026-07-05T09:16:27Z"},{"alias_kind":"pith_short_12","alias_value":"M33TPOSLFJT5","created_at":"2026-07-05T09:16:27Z"},{"alias_kind":"pith_short_16","alias_value":"M33TPOSLFJT5SAZ3","created_at":"2026-07-05T09:16:27Z"},{"alias_kind":"pith_short_8","alias_value":"M33TPOSL","created_at":"2026-07-05T09:16:27Z"}],"graph_snapshots":[{"event_id":"sha256:02a6bdd4dec71578dc4702976dc36d46dea452327744db05471ad6d4a069317e","target":"graph","created_at":"2026-07-05T09:16:27Z","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/2410.04027/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work proposes a simple training-free prompt-free approach to leverage large language models (LLMs) for the Chinese spelling correction (CSC) task, which is totally different from all previous CSC approaches. The key idea is to use an LLM as a pure language model in a conventional manner. The LLM goes through the input sentence from the beginning, and at each inference step, produces a distribution over its vocabulary for deciding the next token, given a partial sentence. To ensure that the output sentence remains faithful to the input sentence, we design a minimal distortion model that ut","authors_text":"Bo Zhang, Chen Li, Fei Huang, Houquan Zhou, Ji Zhang, Min Zhang, Shaopeng Lai, Zhenghua Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-05T04:06:56Z","title":"A Simple yet Effective Training-free Prompt-free Approach to Chinese Spelling Correction Based on Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.04027","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":"sha256:6cbd90bb21beb10af328458c15ceb5d570af2662a5847d2e48f5a0dfff7d3f35","target":"record","created_at":"2026-07-05T09:16:27Z","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":"8d79ffffcb935edca2269d477721f46b1f89982375ca985d8bd0c7308af3addc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-05T04:06:56Z","title_canon_sha256":"e4557d1a608b9b8bb014c4af6cd5187d40f0a8e51b41b86009e09b571e6d5366"},"schema_version":"1.0","source":{"id":"2410.04027","kind":"arxiv","version":1}},"canonical_sha256":"66f737ba4b2a67d9033b25b90f624410779f2949b1fe9828b1a9a0b2fd382e3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66f737ba4b2a67d9033b25b90f624410779f2949b1fe9828b1a9a0b2fd382e3e","first_computed_at":"2026-07-05T09:16:27.995059Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:16:27.995059Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1UzWhQCCQ1g3czBb/QXnXOQyG83+1kvTbuLsoQIKMaElQr8znA7ABYj4zl9uSWrPFqphmx3phMLskndPxASWBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:16:27.995626Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.04027","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6cbd90bb21beb10af328458c15ceb5d570af2662a5847d2e48f5a0dfff7d3f35","sha256:02a6bdd4dec71578dc4702976dc36d46dea452327744db05471ad6d4a069317e"],"state_sha256":"5f5c3eefa003341344ab8f3b0f968dadcf8cd27888a208e8abb14f04b939d1a0"}