{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PMQVUH4WMCBMQQDHE3B2PAAZBO","short_pith_number":"pith:PMQVUH4W","canonical_record":{"source":{"id":"2402.11456","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-18T04:45:01Z","cross_cats_sorted":[],"title_canon_sha256":"98583e613fd10d078ff35aa3ab7fcadc2ece3b1613d8b1b1b087f505a79eea85","abstract_canon_sha256":"56bb30e3a337ca9f4714b0454f013f94538855a3c6879b089db797920cc9fdf4"},"schema_version":"1.0"},"canonical_sha256":"7b215a1f966082c8406726c3a780190b9261b32194a8e8527f182102f221c14b","source":{"kind":"arxiv","id":"2402.11456","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.11456","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"arxiv_version","alias_value":"2402.11456v2","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.11456","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"pith_short_12","alias_value":"PMQVUH4WMCBM","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"pith_short_16","alias_value":"PMQVUH4WMCBMQQDH","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"pith_short_8","alias_value":"PMQVUH4W","created_at":"2026-07-05T08:27:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PMQVUH4WMCBMQQDHE3B2PAAZBO","target":"record","payload":{"canonical_record":{"source":{"id":"2402.11456","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-18T04:45:01Z","cross_cats_sorted":[],"title_canon_sha256":"98583e613fd10d078ff35aa3ab7fcadc2ece3b1613d8b1b1b087f505a79eea85","abstract_canon_sha256":"56bb30e3a337ca9f4714b0454f013f94538855a3c6879b089db797920cc9fdf4"},"schema_version":"1.0"},"canonical_sha256":"7b215a1f966082c8406726c3a780190b9261b32194a8e8527f182102f221c14b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:27:24.813955Z","signature_b64":"AE2qaogOz75TGsNUR69QC4WjZSFPbD6YEOiLInrW53Ug/CvHaZ0+4pRkOU54A2yMpfo0eD0W0Z4GVPqeqqjsBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b215a1f966082c8406726c3a780190b9261b32194a8e8527f182102f221c14b","last_reissued_at":"2026-07-05T08:27:24.813435Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:27:24.813435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.11456","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":"2026-07-05T08:27:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ItSz7rp+xV203epy6C9ukGAvY30JJbhxDlQaTSHacJ9JE3fIIpmR+k92dHH7xfSX1hfIKSPYqQjwDq5Zq/2MBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:43:27.836205Z"},"content_sha256":"4923a6fa6926f54fa833e6ea03071ee9a0c501a42f55151706da5c81fa0e363c","schema_version":"1.0","event_id":"sha256:4923a6fa6926f54fa833e6ea03071ee9a0c501a42f55151706da5c81fa0e363c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PMQVUH4WMCBMQQDHE3B2PAAZBO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Byron C Wallace, Hannah Louisa G\\\"oke, Jan Trienes, Junyi Jessy Li, Lily Chen, Monika Coers, Sebastian Antony Joseph, Wei Xu","submitted_at":"2024-02-18T04:45:01Z","abstract_excerpt":"Plain language summarization with LLMs can be useful for improving textual accessibility of technical content. But how factual are these summaries in a high-stakes domain like medicine? This paper presents FactPICO, a factuality benchmark for plain language summarization of medical texts describing randomized controlled trials (RCTs), which are the basis of evidence-based medicine and can directly inform patient treatment. FactPICO consists of 345 plain language summaries of RCT abstracts generated from three LLMs (i.e., GPT-4, Llama-2, and Alpaca), with fine-grained evaluation and natural lan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.11456","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/2402.11456/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":"2026-07-05T08:27:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tys7e7Dp7iq3CyQrseHA7OtmoYx8yZ2/QLkDdCsDe/9YBhfEXZBs19DXqKVu0PbFud7w3L5GV8AujrO4qADaAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:43:27.836719Z"},"content_sha256":"53532e2632b22c99ad9a0d45a8435de55471614c9c0701b0b4105269756e497a","schema_version":"1.0","event_id":"sha256:53532e2632b22c99ad9a0d45a8435de55471614c9c0701b0b4105269756e497a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO/bundle.json","state_url":"https://pith.science/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO/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":"2026-08-04T13:43:27Z","links":{"resolver":"https://pith.science/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO","bundle":"https://pith.science/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO/bundle.json","state":"https://pith.science/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PMQVUH4WMCBMQQDHE3B2PAAZBO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PMQVUH4WMCBMQQDHE3B2PAAZBO","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":"56bb30e3a337ca9f4714b0454f013f94538855a3c6879b089db797920cc9fdf4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-18T04:45:01Z","title_canon_sha256":"98583e613fd10d078ff35aa3ab7fcadc2ece3b1613d8b1b1b087f505a79eea85"},"schema_version":"1.0","source":{"id":"2402.11456","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.11456","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"arxiv_version","alias_value":"2402.11456v2","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.11456","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"pith_short_12","alias_value":"PMQVUH4WMCBM","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"pith_short_16","alias_value":"PMQVUH4WMCBMQQDH","created_at":"2026-07-05T08:27:24Z"},{"alias_kind":"pith_short_8","alias_value":"PMQVUH4W","created_at":"2026-07-05T08:27:24Z"}],"graph_snapshots":[{"event_id":"sha256:53532e2632b22c99ad9a0d45a8435de55471614c9c0701b0b4105269756e497a","target":"graph","created_at":"2026-07-05T08:27:24Z","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/2402.11456/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Plain language summarization with LLMs can be useful for improving textual accessibility of technical content. But how factual are these summaries in a high-stakes domain like medicine? This paper presents FactPICO, a factuality benchmark for plain language summarization of medical texts describing randomized controlled trials (RCTs), which are the basis of evidence-based medicine and can directly inform patient treatment. FactPICO consists of 345 plain language summaries of RCT abstracts generated from three LLMs (i.e., GPT-4, Llama-2, and Alpaca), with fine-grained evaluation and natural lan","authors_text":"Byron C Wallace, Hannah Louisa G\\\"oke, Jan Trienes, Junyi Jessy Li, Lily Chen, Monika Coers, Sebastian Antony Joseph, Wei Xu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-18T04:45:01Z","title":"FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.11456","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":"sha256:4923a6fa6926f54fa833e6ea03071ee9a0c501a42f55151706da5c81fa0e363c","target":"record","created_at":"2026-07-05T08:27:24Z","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":"56bb30e3a337ca9f4714b0454f013f94538855a3c6879b089db797920cc9fdf4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-18T04:45:01Z","title_canon_sha256":"98583e613fd10d078ff35aa3ab7fcadc2ece3b1613d8b1b1b087f505a79eea85"},"schema_version":"1.0","source":{"id":"2402.11456","kind":"arxiv","version":2}},"canonical_sha256":"7b215a1f966082c8406726c3a780190b9261b32194a8e8527f182102f221c14b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b215a1f966082c8406726c3a780190b9261b32194a8e8527f182102f221c14b","first_computed_at":"2026-07-05T08:27:24.813435Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:27:24.813435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AE2qaogOz75TGsNUR69QC4WjZSFPbD6YEOiLInrW53Ug/CvHaZ0+4pRkOU54A2yMpfo0eD0W0Z4GVPqeqqjsBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:27:24.813955Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.11456","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4923a6fa6926f54fa833e6ea03071ee9a0c501a42f55151706da5c81fa0e363c","sha256:53532e2632b22c99ad9a0d45a8435de55471614c9c0701b0b4105269756e497a"],"state_sha256":"526554ab312a0b7de364c2eae1f9dd8ef07f30837fbd031f626d9a6a740a41c2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KMXFGKY32LrTHQyM89edf0eQhFZ7ii/vbS8hSTo/4kOKOAmbxSdERdo46ki7d3PrpiszmJ/Ka0g5Hpf5IR20DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T13:43:27.842648Z","bundle_sha256":"c04da3038def98caa55d90a069ced0e1e6ad1bec1dfb6a2570f871766ab7b424"}}