{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5IDT436AS52NBPVOHHEVVT4CSK","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":"42806f77ebe6749def0ea8b7a0f6ba626ed1dc5b00646a3e39fb3f73690f3a13","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T07:58:12Z","title_canon_sha256":"9e0a9168dedddfb637cad1b89224f5bf385b8dc34c7d7dffa32363aa516c2866"},"schema_version":"1.0","source":{"id":"2402.16379","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.16379","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"arxiv_version","alias_value":"2402.16379v3","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.16379","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_12","alias_value":"5IDT436AS52N","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_16","alias_value":"5IDT436AS52NBPVO","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_8","alias_value":"5IDT436A","created_at":"2026-07-05T08:35:00Z"}],"graph_snapshots":[{"event_id":"sha256:0d24581225fa3d4be2f1597f93905757bb83b5285c94c2e78a25ade5c77c202e","target":"graph","created_at":"2026-07-05T08:35:00Z","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/2402.16379/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have achieved impressive results in Machine Translation (MT). However, careful evaluations by human reveal that the translations produced by LLMs still contain multiple errors. Importantly, feeding back such error information into the LLMs can lead to self-refinement and result in improved translation performance. Motivated by these insights, we introduce a systematic LLM-based self-refinement translation framework, named \\textbf{TEaR}, which stands for \\textbf{T}ranslate, \\textbf{E}stimate, \\textbf{a}nd \\textbf{R}efine, marking a significant step forward in this d","authors_text":"Bei Wu, Hao Li, Jian Wu, Jiayu Liao, Jun Lang, Wenqiang Liu, Yang Feng, Yan Zhang, Zhaopeng Feng, Zuozhu Liu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T07:58:12Z","title":"TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.16379","kind":"arxiv","version":3},"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":"sha256:34d06a170b436dd82c88903b91d5a4a1a362baaea557afcce52c6cdd9d2646c7","target":"record","created_at":"2026-07-05T08:35:00Z","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":"42806f77ebe6749def0ea8b7a0f6ba626ed1dc5b00646a3e39fb3f73690f3a13","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T07:58:12Z","title_canon_sha256":"9e0a9168dedddfb637cad1b89224f5bf385b8dc34c7d7dffa32363aa516c2866"},"schema_version":"1.0","source":{"id":"2402.16379","kind":"arxiv","version":3}},"canonical_sha256":"ea073e6fc09774d0beae39c95acf82928a80fbb9b430c920b6bbaf3bc85a6880","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ea073e6fc09774d0beae39c95acf82928a80fbb9b430c920b6bbaf3bc85a6880","first_computed_at":"2026-07-05T08:35:00.572610Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:35:00.572610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ybkYCNsG5i8HpRXta+cCVnw0aGPZfL8lLH3Cq4Tv4x2wStPYZcFIpx3DuK5CzLl/s0/V/FBACutKbSRLZFu+Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:35:00.573050Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.16379","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:34d06a170b436dd82c88903b91d5a4a1a362baaea557afcce52c6cdd9d2646c7","sha256:0d24581225fa3d4be2f1597f93905757bb83b5285c94c2e78a25ade5c77c202e"],"state_sha256":"1d1fdea0177cd2988c9add6adf75fd5833d8c1140c9c3268ae1226359fe58c47"}