{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TZCWZSNYYT2YR6L6M6BPFW32HB","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":"1d1b765f947fefdfcba6a6b2f49e6a25f5671894e94f1b0a5f0e6312c5dfaaee","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-05T18:26:14Z","title_canon_sha256":"6040798e2b7e9f3ab58dd60b1ac354fc1b50a0362af4ce49164a14c49a31d66d"},"schema_version":"1.0","source":{"id":"2506.05497","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05497","created_at":"2026-07-05T11:17:03Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05497v1","created_at":"2026-07-05T11:17:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05497","created_at":"2026-07-05T11:17:03Z"},{"alias_kind":"pith_short_12","alias_value":"TZCWZSNYYT2Y","created_at":"2026-07-05T11:17:03Z"},{"alias_kind":"pith_short_16","alias_value":"TZCWZSNYYT2YR6L6","created_at":"2026-07-05T11:17:03Z"},{"alias_kind":"pith_short_8","alias_value":"TZCWZSNY","created_at":"2026-07-05T11:17:03Z"}],"graph_snapshots":[{"event_id":"sha256:0b300a71bf78873bbd8394a6f10c5ca79097541bd687d85340cc059dd53fecc9","target":"graph","created_at":"2026-07-05T11:17:03Z","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/2506.05497/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Uncertainty quantification (UQ) is essential for safe deployment of generative AI models such as large language models (LLMs), especially in high stakes applications. Conformal prediction (CP) offers a principled uncertainty quantification framework, but classical methods focus on regression and classification, relying on geometric distances or softmax scores: tools that presuppose structured outputs. We depart from this paradigm by studying CP in a query only setting, where prediction sets must be constructed solely from finite queries to a black box generative model, introducing a new trade ","authors_text":"George Pappas, Hamed Hassani, Shayan Kiyani, Sima Noorani","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-05T18:26:14Z","title":"Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05497","kind":"arxiv","version":1},"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":"sha256:99bff746a02e2f2b93e174e5d5cb57c309b5dd534f9a4c04008e101b5e3f7768","target":"record","created_at":"2026-07-05T11:17:03Z","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":"1d1b765f947fefdfcba6a6b2f49e6a25f5671894e94f1b0a5f0e6312c5dfaaee","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-05T18:26:14Z","title_canon_sha256":"6040798e2b7e9f3ab58dd60b1ac354fc1b50a0362af4ce49164a14c49a31d66d"},"schema_version":"1.0","source":{"id":"2506.05497","kind":"arxiv","version":1}},"canonical_sha256":"9e456cc9b8c4f588f97e6782f2db7a387918b963f3908d109aac0a53bd22e228","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9e456cc9b8c4f588f97e6782f2db7a387918b963f3908d109aac0a53bd22e228","first_computed_at":"2026-07-05T11:17:03.787742Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:03.787742Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l87B3TOzxMoBm9q2NmY4hn9lE/viwgVH8ndy9jj+H8BmkFRJ8PtWMHmh6ykNlrAXetRv6MM9L/V6faDyIRHSCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:03.788279Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05497","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:99bff746a02e2f2b93e174e5d5cb57c309b5dd534f9a4c04008e101b5e3f7768","sha256:0b300a71bf78873bbd8394a6f10c5ca79097541bd687d85340cc059dd53fecc9"],"state_sha256":"a771fd43c45d0f6ebaca7108c3dbd070325d6add0463330bf4a518e3845beb13"}