{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DU4WN2XHMNZV6ROKUBJRTBE2RE","short_pith_number":"pith:DU4WN2XH","canonical_record":{"source":{"id":"2411.05980","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-08T21:26:57Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"a876fefcfae6ffaf8c4c2e31822b741e413cc60558c0923a69a424c09807d71c","abstract_canon_sha256":"a71ec5c890dd8390f4e3b9988cedb72afb2154564b654d8e0a906a1ee455e700"},"schema_version":"1.0"},"canonical_sha256":"1d3966eae763735f45caa05319849a891ada092b9debb811f063084f3b0451b8","source":{"kind":"arxiv","id":"2411.05980","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.05980","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"arxiv_version","alias_value":"2411.05980v3","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.05980","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"pith_short_12","alias_value":"DU4WN2XHMNZV","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"pith_short_16","alias_value":"DU4WN2XHMNZV6ROK","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"pith_short_8","alias_value":"DU4WN2XH","created_at":"2026-07-05T11:13:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DU4WN2XHMNZV6ROKUBJRTBE2RE","target":"record","payload":{"canonical_record":{"source":{"id":"2411.05980","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-08T21:26:57Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"a876fefcfae6ffaf8c4c2e31822b741e413cc60558c0923a69a424c09807d71c","abstract_canon_sha256":"a71ec5c890dd8390f4e3b9988cedb72afb2154564b654d8e0a906a1ee455e700"},"schema_version":"1.0"},"canonical_sha256":"1d3966eae763735f45caa05319849a891ada092b9debb811f063084f3b0451b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:15.622174Z","signature_b64":"BCQgI00QZbSgMT8F0GsWAHeeAIXfJcLBGwjEM+39TBIqlMlGqjkjj5BsQP11NA6DiXXEnC5eH2KhxCCpr5WnDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1d3966eae763735f45caa05319849a891ada092b9debb811f063084f3b0451b8","last_reissued_at":"2026-07-05T11:13:15.621592Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:15.621592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.05980","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:13:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HI/D6d4axDHLKS/LWBe2vlb/nb8VL18dstCcZEoEqgp+5TUzTkiF5v+LMQFhMk4haNdIvWeLsFdzNz9OqUgtBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T17:06:38.978431Z"},"content_sha256":"0e1cfb62c88fbcad38082a7a1a8e72506d62daefc93fa3fa3b3a7473fc7de220","schema_version":"1.0","event_id":"sha256:0e1cfb62c88fbcad38082a7a1a8e72506d62daefc93fa3fa3b3a7473fc7de220"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DU4WN2XHMNZV6ROKUBJRTBE2RE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FactLens: Benchmarking Fine-Grained Fact Verification","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Dan Zhang, Estevam Hruschka, Kushan Mitra, Sajjadur Rahman","submitted_at":"2024-11-08T21:26:57Z","abstract_excerpt":"Large Language Models (LLMs) have shown impressive capability in language generation and understanding, but their tendency to hallucinate and produce factually incorrect information remains a key limitation. To verify LLM-generated contents and claims from other sources, traditional verification approaches often rely on holistic models that assign a single factuality label to complex claims, potentially obscuring nuanced errors. In this paper, we advocate for a shift towards fine-grained verification, where complex claims are broken down into smaller sub-claims for individual verification, all"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.05980","kind":"arxiv","version":3},"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/2411.05980/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":"2026-07-05T11:13:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cBHno8s4vnVkb01ki9xN0pvXTxJtFoyCiGcDXqB2/oEzXu2BNzPzraQt4MLFX+4PoOZ+iTRi85O9kI2qYEltBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T17:06:38.979020Z"},"content_sha256":"4d0f4c0bd86a51e9bbadcb3f961c68cfe97753bac1d54a8bf9c7217452823f3a","schema_version":"1.0","event_id":"sha256:4d0f4c0bd86a51e9bbadcb3f961c68cfe97753bac1d54a8bf9c7217452823f3a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE/bundle.json","state_url":"https://pith.science/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE/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":"2026-08-07T17:06:38Z","links":{"resolver":"https://pith.science/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE","bundle":"https://pith.science/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE/bundle.json","state":"https://pith.science/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DU4WN2XHMNZV6ROKUBJRTBE2RE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DU4WN2XHMNZV6ROKUBJRTBE2RE","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":"a71ec5c890dd8390f4e3b9988cedb72afb2154564b654d8e0a906a1ee455e700","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-08T21:26:57Z","title_canon_sha256":"a876fefcfae6ffaf8c4c2e31822b741e413cc60558c0923a69a424c09807d71c"},"schema_version":"1.0","source":{"id":"2411.05980","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.05980","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"arxiv_version","alias_value":"2411.05980v3","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.05980","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"pith_short_12","alias_value":"DU4WN2XHMNZV","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"pith_short_16","alias_value":"DU4WN2XHMNZV6ROK","created_at":"2026-07-05T11:13:15Z"},{"alias_kind":"pith_short_8","alias_value":"DU4WN2XH","created_at":"2026-07-05T11:13:15Z"}],"graph_snapshots":[{"event_id":"sha256:4d0f4c0bd86a51e9bbadcb3f961c68cfe97753bac1d54a8bf9c7217452823f3a","target":"graph","created_at":"2026-07-05T11:13:15Z","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/2411.05980/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have shown impressive capability in language generation and understanding, but their tendency to hallucinate and produce factually incorrect information remains a key limitation. To verify LLM-generated contents and claims from other sources, traditional verification approaches often rely on holistic models that assign a single factuality label to complex claims, potentially obscuring nuanced errors. In this paper, we advocate for a shift towards fine-grained verification, where complex claims are broken down into smaller sub-claims for individual verification, all","authors_text":"Dan Zhang, Estevam Hruschka, Kushan Mitra, Sajjadur Rahman","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-08T21:26:57Z","title":"FactLens: Benchmarking Fine-Grained Fact Verification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.05980","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":"sha256:0e1cfb62c88fbcad38082a7a1a8e72506d62daefc93fa3fa3b3a7473fc7de220","target":"record","created_at":"2026-07-05T11:13:15Z","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":"a71ec5c890dd8390f4e3b9988cedb72afb2154564b654d8e0a906a1ee455e700","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-11-08T21:26:57Z","title_canon_sha256":"a876fefcfae6ffaf8c4c2e31822b741e413cc60558c0923a69a424c09807d71c"},"schema_version":"1.0","source":{"id":"2411.05980","kind":"arxiv","version":3}},"canonical_sha256":"1d3966eae763735f45caa05319849a891ada092b9debb811f063084f3b0451b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d3966eae763735f45caa05319849a891ada092b9debb811f063084f3b0451b8","first_computed_at":"2026-07-05T11:13:15.621592Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:15.621592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BCQgI00QZbSgMT8F0GsWAHeeAIXfJcLBGwjEM+39TBIqlMlGqjkjj5BsQP11NA6DiXXEnC5eH2KhxCCpr5WnDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:15.622174Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.05980","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0e1cfb62c88fbcad38082a7a1a8e72506d62daefc93fa3fa3b3a7473fc7de220","sha256:4d0f4c0bd86a51e9bbadcb3f961c68cfe97753bac1d54a8bf9c7217452823f3a"],"state_sha256":"30cbaf95c1e4a57b0caa8a381aee396aeaaf9b10e8216278b2b95b50d99f4137"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lfVxLo79LdvsvdtXM1eE4caSMkRdiRjCSquVQP3GJOaE4UeoTWiJkusfEJAr8/l8Ou5NT6bWaVqvmJ8g4NtAAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T17:06:38.983129Z","bundle_sha256":"3a7e01070e40da87e4fa222d50bca17392699d1bd0c5a5b4a8575b0b23d28e77"}}