{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:EKU64Y6456I2ULTVGIQUJUQ6EP","short_pith_number":"pith:EKU64Y64","canonical_record":{"source":{"id":"2311.18580","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-30T14:18:47Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"cfec86f75280acc35d144a1b72de80bb91e966b98d9cfccf1429770c1735e61a","abstract_canon_sha256":"6b42c660b837969ed827cb91593dd95efb9ea009a293821156fd0eaf7012a3e7"},"schema_version":"1.0"},"canonical_sha256":"22a9ee63dcef91aa2e75322144d21e23fa2d0eba392ee88b2586a35b1c3d1b13","source":{"kind":"arxiv","id":"2311.18580","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.18580","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"arxiv_version","alias_value":"2311.18580v2","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.18580","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"pith_short_12","alias_value":"EKU64Y6456I2","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"pith_short_16","alias_value":"EKU64Y6456I2ULTV","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"pith_short_8","alias_value":"EKU64Y64","created_at":"2026-07-05T09:52:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:EKU64Y6456I2ULTVGIQUJUQ6EP","target":"record","payload":{"canonical_record":{"source":{"id":"2311.18580","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-30T14:18:47Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"cfec86f75280acc35d144a1b72de80bb91e966b98d9cfccf1429770c1735e61a","abstract_canon_sha256":"6b42c660b837969ed827cb91593dd95efb9ea009a293821156fd0eaf7012a3e7"},"schema_version":"1.0"},"canonical_sha256":"22a9ee63dcef91aa2e75322144d21e23fa2d0eba392ee88b2586a35b1c3d1b13","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:52:58.469397Z","signature_b64":"nRvHXMoK8P242KUrPDSWpR1MpIG1I67icedOqH1wG7TO6hTmqouOuea1O08J5jq0qq8nkG6k5MxK1c8BFqolBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22a9ee63dcef91aa2e75322144d21e23fa2d0eba392ee88b2586a35b1c3d1b13","last_reissued_at":"2026-07-05T09:52:58.468889Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:52:58.468889Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.18580","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:52:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dv4gqm4EjscNTMBdJ+AIvvJnswwYniDOR3ZF+eG7m2gOPpFU6FwjgqEOnJkodMslAPgyCe5YdGmF0lUB9WCsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T02:12:31.656583Z"},"content_sha256":"738334d334d694cf247106065d7fa0d38bf0ef49d5183d9719b7b74708802218","schema_version":"1.0","event_id":"sha256:738334d334d694cf247106065d7fa0d38bf0ef49d5183d9719b7b74708802218"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:EKU64Y6456I2ULTVGIQUJUQ6EP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, Toxicity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.CL","authors_text":"Shiyao Cui, Siqi Wang, Tianyun Liu, Tingwen Liu, Wenyuan Zhang, Yilong Chen, Zhenyu Zhang","submitted_at":"2023-11-30T14:18:47Z","abstract_excerpt":"The widespread of generative artificial intelligence has heightened concerns about the potential harms posed by AI-generated texts, primarily stemming from factoid, unfair, and toxic content. Previous researchers have invested much effort in assessing the harmlessness of generative language models. However, existing benchmarks are struggling in the era of large language models (LLMs), due to the stronger language generation and instruction following capabilities, as well as wider applications. In this paper, we propose FFT, a new benchmark with 2116 elaborated-designed instances, for LLM harml"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.18580","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.18580/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:52:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6ang55yiIE3E6JgNSSQ5yT6r8qJ0M5/lIIHT66QAmcOdlTIs6QLvfDFFwCHmp6SFNgoSzPi4aMkoK81bOg8+Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T02:12:31.657041Z"},"content_sha256":"45c60694a9cbccf8cd47ce443ce532ac49590e320314545a4e5b738031dde470","schema_version":"1.0","event_id":"sha256:45c60694a9cbccf8cd47ce443ce532ac49590e320314545a4e5b738031dde470"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EKU64Y6456I2ULTVGIQUJUQ6EP/bundle.json","state_url":"https://pith.science/pith/EKU64Y6456I2ULTVGIQUJUQ6EP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EKU64Y6456I2ULTVGIQUJUQ6EP/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-22T02:12:31Z","links":{"resolver":"https://pith.science/pith/EKU64Y6456I2ULTVGIQUJUQ6EP","bundle":"https://pith.science/pith/EKU64Y6456I2ULTVGIQUJUQ6EP/bundle.json","state":"https://pith.science/pith/EKU64Y6456I2ULTVGIQUJUQ6EP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EKU64Y6456I2ULTVGIQUJUQ6EP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:EKU64Y6456I2ULTVGIQUJUQ6EP","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":"6b42c660b837969ed827cb91593dd95efb9ea009a293821156fd0eaf7012a3e7","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-30T14:18:47Z","title_canon_sha256":"cfec86f75280acc35d144a1b72de80bb91e966b98d9cfccf1429770c1735e61a"},"schema_version":"1.0","source":{"id":"2311.18580","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.18580","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"arxiv_version","alias_value":"2311.18580v2","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.18580","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"pith_short_12","alias_value":"EKU64Y6456I2","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"pith_short_16","alias_value":"EKU64Y6456I2ULTV","created_at":"2026-07-05T09:52:58Z"},{"alias_kind":"pith_short_8","alias_value":"EKU64Y64","created_at":"2026-07-05T09:52:58Z"}],"graph_snapshots":[{"event_id":"sha256:45c60694a9cbccf8cd47ce443ce532ac49590e320314545a4e5b738031dde470","target":"graph","created_at":"2026-07-05T09:52:58Z","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/2311.18580/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The widespread of generative artificial intelligence has heightened concerns about the potential harms posed by AI-generated texts, primarily stemming from factoid, unfair, and toxic content. Previous researchers have invested much effort in assessing the harmlessness of generative language models. However, existing benchmarks are struggling in the era of large language models (LLMs), due to the stronger language generation and instruction following capabilities, as well as wider applications. In this paper, we propose FFT, a new benchmark with 2116 elaborated-designed instances, for LLM harml","authors_text":"Shiyao Cui, Siqi Wang, Tianyun Liu, Tingwen Liu, Wenyuan Zhang, Yilong Chen, Zhenyu Zhang","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-30T14:18:47Z","title":"FFT: Towards Harmlessness Evaluation and Analysis for LLMs with Factuality, Fairness, Toxicity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.18580","kind":"arxiv","version":2},"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":"sha256:738334d334d694cf247106065d7fa0d38bf0ef49d5183d9719b7b74708802218","target":"record","created_at":"2026-07-05T09:52:58Z","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":"6b42c660b837969ed827cb91593dd95efb9ea009a293821156fd0eaf7012a3e7","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-30T14:18:47Z","title_canon_sha256":"cfec86f75280acc35d144a1b72de80bb91e966b98d9cfccf1429770c1735e61a"},"schema_version":"1.0","source":{"id":"2311.18580","kind":"arxiv","version":2}},"canonical_sha256":"22a9ee63dcef91aa2e75322144d21e23fa2d0eba392ee88b2586a35b1c3d1b13","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22a9ee63dcef91aa2e75322144d21e23fa2d0eba392ee88b2586a35b1c3d1b13","first_computed_at":"2026-07-05T09:52:58.468889Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:52:58.468889Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nRvHXMoK8P242KUrPDSWpR1MpIG1I67icedOqH1wG7TO6hTmqouOuea1O08J5jq0qq8nkG6k5MxK1c8BFqolBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:52:58.469397Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.18580","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:738334d334d694cf247106065d7fa0d38bf0ef49d5183d9719b7b74708802218","sha256:45c60694a9cbccf8cd47ce443ce532ac49590e320314545a4e5b738031dde470"],"state_sha256":"7e39a2731ebddc85d6df39d6ea0f0727895e570b9d0d67876f50ae216dd023b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UxcaJUxrf+wdlujt5UHedZpj1Z3bdF1M1PcvksKcyiCwBQpJL+MJi1j+GX6cAj+w8PlZLd1H27oCBOoAy1RRCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T02:12:31.659803Z","bundle_sha256":"5b92595bd1ba784ec0c4d04ce63bf825302adca1757fc99623a756c98265a1e4"}}