{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:W5VR4VBI2HR34EPHIZJIOB7HN5","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":"82511187ef0c0435d076f5ccbbbe4ec55efe74dc8fdc6f9cc357432e0a197175","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-30T16:31:26Z","title_canon_sha256":"f98286f4f2c63ea75a183bd92178a1ced7591baf888752360fa0d8d40548fa52"},"schema_version":"1.0","source":{"id":"2305.19187","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.19187","created_at":"2026-07-05T08:20:22Z"},{"alias_kind":"arxiv_version","alias_value":"2305.19187v3","created_at":"2026-07-05T08:20:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.19187","created_at":"2026-07-05T08:20:22Z"},{"alias_kind":"pith_short_12","alias_value":"W5VR4VBI2HR3","created_at":"2026-07-05T08:20:22Z"},{"alias_kind":"pith_short_16","alias_value":"W5VR4VBI2HR34EPH","created_at":"2026-07-05T08:20:22Z"},{"alias_kind":"pith_short_8","alias_value":"W5VR4VBI","created_at":"2026-07-05T08:20:22Z"}],"graph_snapshots":[{"event_id":"sha256:82ee9545655300112b62d39c11c393a31f0806fb3d869b49eed27fe7dc25876e","target":"graph","created_at":"2026-07-05T08:20:22Z","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/2305.19187/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) specializing in natural language generation (NLG) have recently started exhibiting promising capabilities across a variety of domains. However, gauging the trustworthiness of responses generated by LLMs remains an open challenge, with limited research on uncertainty quantification (UQ) for NLG. Furthermore, existing literature typically assumes white-box access to language models, which is becoming unrealistic either due to the closed-source nature of the latest LLMs or computational constraints. In this work, we investigate UQ in NLG for *black-box* LLMs. We first","authors_text":"Jimeng Sun, Shubhendu Trivedi, Zhen Lin","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-30T16:31:26Z","title":"Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.19187","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:af9987cc7be3f6df3623bed2cdb2cbdc6f907877ef1909f16e3f17f9f492e7a4","target":"record","created_at":"2026-07-05T08:20:22Z","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":"82511187ef0c0435d076f5ccbbbe4ec55efe74dc8fdc6f9cc357432e0a197175","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-30T16:31:26Z","title_canon_sha256":"f98286f4f2c63ea75a183bd92178a1ced7591baf888752360fa0d8d40548fa52"},"schema_version":"1.0","source":{"id":"2305.19187","kind":"arxiv","version":3}},"canonical_sha256":"b76b1e5428d1e3be11e746528707e76f5b934e501991735be20089de8d50a07b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b76b1e5428d1e3be11e746528707e76f5b934e501991735be20089de8d50a07b","first_computed_at":"2026-07-05T08:20:22.926022Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:20:22.926022Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"khwnV+blgB4NsXTW3dUT5zBhhG1V4X2ohRj4SMrXopMbcKa3kM9CI9e1PFS2g0fwPw5eG2+dpu7qWvQYmp8MBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:20:22.926532Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.19187","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af9987cc7be3f6df3623bed2cdb2cbdc6f907877ef1909f16e3f17f9f492e7a4","sha256:82ee9545655300112b62d39c11c393a31f0806fb3d869b49eed27fe7dc25876e"],"state_sha256":"0d5c44273c0cfea7bfd3580f6bc158dff0e9f5dd348d3ede002c0a9b3ece3263"}