{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WVEEJYZCDTRZ2L656LCPPM6M4J","short_pith_number":"pith:WVEEJYZC","schema_version":"1.0","canonical_sha256":"b54844e3221ce39d2fddf2c4f7b3cce27f538cd215db89947cd737a8dc369d7e","source":{"kind":"arxiv","id":"2309.05138","version":3},"attestation_state":"computed","paper":{"title":"GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.CR","authors_text":"Aamir Hamid, Hemanth Reddy Samidi, Primal Pappachan, Roberto Yus, Tim Finin","submitted_at":"2023-09-10T21:15:42Z","abstract_excerpt":"Privacy policies of websites are often lengthy and intricate. Privacy assistants assist in simplifying policies and making them more accessible and user friendly. The emergence of generative AI (genAI) offers new opportunities to build privacy assistants that can answer users questions about privacy policies. However, genAIs reliability is a concern due to its potential for producing inaccurate information. This study introduces GenAIPABench, a benchmark for evaluating Generative AI-based Privacy Assistants (GenAIPAs). GenAIPABench includes: 1) A set of questions about privacy policies and dat"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2309.05138","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CR","submitted_at":"2023-09-10T21:15:42Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"7dcab1d600424b08dc5117d40b93d0151546aba022ff8ed00764a2977b981fbf","abstract_canon_sha256":"f7d56f40c831488dc8cfae16b36a5e0f83d830bc8f71192aa423e519f5a20001"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:25:45.667897Z","signature_b64":"Iu7N9x1KuhhHbVeLQzqG2psrNGuN+2C/IsLLVZyFaFYG9wiQUGQBbpC9gGXt+fN5dOwZ5GhO2wzugOFqZWQKBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b54844e3221ce39d2fddf2c4f7b3cce27f538cd215db89947cd737a8dc369d7e","last_reissued_at":"2026-07-05T07:25:45.667440Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:25:45.667440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.CR","authors_text":"Aamir Hamid, Hemanth Reddy Samidi, Primal Pappachan, Roberto Yus, Tim Finin","submitted_at":"2023-09-10T21:15:42Z","abstract_excerpt":"Privacy policies of websites are often lengthy and intricate. Privacy assistants assist in simplifying policies and making them more accessible and user friendly. The emergence of generative AI (genAI) offers new opportunities to build privacy assistants that can answer users questions about privacy policies. However, genAIs reliability is a concern due to its potential for producing inaccurate information. This study introduces GenAIPABench, a benchmark for evaluating Generative AI-based Privacy Assistants (GenAIPAs). GenAIPABench includes: 1) A set of questions about privacy policies and dat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.05138","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/2309.05138/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2309.05138","created_at":"2026-07-05T07:25:45.667490+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.05138v3","created_at":"2026-07-05T07:25:45.667490+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.05138","created_at":"2026-07-05T07:25:45.667490+00:00"},{"alias_kind":"pith_short_12","alias_value":"WVEEJYZCDTRZ","created_at":"2026-07-05T07:25:45.667490+00:00"},{"alias_kind":"pith_short_16","alias_value":"WVEEJYZCDTRZ2L65","created_at":"2026-07-05T07:25:45.667490+00:00"},{"alias_kind":"pith_short_8","alias_value":"WVEEJYZC","created_at":"2026-07-05T07:25:45.667490+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J","json":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J.json","graph_json":"https://pith.science/api/pith-number/WVEEJYZCDTRZ2L656LCPPM6M4J/graph.json","events_json":"https://pith.science/api/pith-number/WVEEJYZCDTRZ2L656LCPPM6M4J/events.json","paper":"https://pith.science/paper/WVEEJYZC"},"agent_actions":{"view_html":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J","download_json":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J.json","view_paper":"https://pith.science/paper/WVEEJYZC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.05138&json=true","fetch_graph":"https://pith.science/api/pith-number/WVEEJYZCDTRZ2L656LCPPM6M4J/graph.json","fetch_events":"https://pith.science/api/pith-number/WVEEJYZCDTRZ2L656LCPPM6M4J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J/action/storage_attestation","attest_author":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J/action/author_attestation","sign_citation":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J/action/citation_signature","submit_replication":"https://pith.science/pith/WVEEJYZCDTRZ2L656LCPPM6M4J/action/replication_record"}},"created_at":"2026-07-05T07:25:45.667490+00:00","updated_at":"2026-07-05T07:25:45.667490+00:00"}