{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:UJLLHCC2MTNF47GHYGMKUM7S4I","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":"bb87b5f48aa8510736a5441df5c4468eb60beaddbed9d90dc9fd2b566126aa89","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-07T13:34:21Z","title_canon_sha256":"a651f19baec0b3eb43843a0d184ed512ec47de9ab813039ae125aa98727b4fdf"},"schema_version":"1.0","source":{"id":"2310.04799","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.04799","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"arxiv_version","alias_value":"2310.04799v3","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.04799","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_12","alias_value":"UJLLHCC2MTNF","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_16","alias_value":"UJLLHCC2MTNF47GH","created_at":"2026-07-05T08:28:34Z"},{"alias_kind":"pith_short_8","alias_value":"UJLLHCC2","created_at":"2026-07-05T08:28:34Z"}],"graph_snapshots":[{"event_id":"sha256:ede70534f721f4bc0bfdb43dc688ee7a2b1c1ea98af1bb7c1c3fb8a6e3763c3f","target":"graph","created_at":"2026-07-05T08:28:34Z","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/2310.04799/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, the development of open-source large language models (LLMs) has advanced rapidly. Nevertheless, due to data constraints, the capabilities of most open-source LLMs are primarily focused on English. To address this issue, we introduce the concept of $\\textit{chat vector}$ to equip pre-trained language models with instruction following and human value alignment via simple model arithmetic. The chat vector is derived by subtracting the weights of a pre-trained base model (e.g. LLaMA2) from those of its corresponding chat model (e.g. LLaMA2-chat). By simply adding the chat vector to a con","authors_text":"Hung-yi Lee, Kuang-Ming Chen, Pin-Zu Li, Richard Tzong-Han Tsai, Shih-Cheng Huang, Shih-Kai Hsiao, Yu-Chi Hsu, Yu Tung Lin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-07T13:34:21Z","title":"Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.04799","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":"sha256:597382e2ebddec31d1a014e8d0340e9025443a6764a6a922166441bf4c3a695b","target":"record","created_at":"2026-07-05T08:28:34Z","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":"bb87b5f48aa8510736a5441df5c4468eb60beaddbed9d90dc9fd2b566126aa89","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-07T13:34:21Z","title_canon_sha256":"a651f19baec0b3eb43843a0d184ed512ec47de9ab813039ae125aa98727b4fdf"},"schema_version":"1.0","source":{"id":"2310.04799","kind":"arxiv","version":3}},"canonical_sha256":"a256b3885a64da5e7cc7c198aa33f2e20ed04291176e673fe2e4a3a2fe0c5d8d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a256b3885a64da5e7cc7c198aa33f2e20ed04291176e673fe2e4a3a2fe0c5d8d","first_computed_at":"2026-07-05T08:28:34.052164Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:28:34.052164Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dEO7tyDqVFlWiaJ0+TYmkumtYmkwQHDRVpJyx+FuEaxNm6klRm5ONAXiefimzA7UKwHHDrwXvO4Axp3bWNfMCg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:28:34.052638Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.04799","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:597382e2ebddec31d1a014e8d0340e9025443a6764a6a922166441bf4c3a695b","sha256:ede70534f721f4bc0bfdb43dc688ee7a2b1c1ea98af1bb7c1c3fb8a6e3763c3f"],"state_sha256":"0186b9d79d0ab85e4403e7632a9637f73b35fd0e9e555c97f12115216f5808ed"}