{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:KFH6FBB6HHGKTAQEOHQMYOCPGY","short_pith_number":"pith:KFH6FBB6","canonical_record":{"source":{"id":"2602.07253","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-02-06T23:05:48Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"7e8fa1d306afd600f28217644fa8940308becb3183c85a10ca69916a88b62c03","abstract_canon_sha256":"b74c620517faa4a0982038809784881c808697ce1e1bb0574d5c449481fce2f4"},"schema_version":"1.0"},"canonical_sha256":"514fe2843e39cca9820471e0cc384f3623785efe1f73d9c9229d925d2fa95d46","source":{"kind":"arxiv","id":"2602.07253","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.07253","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"arxiv_version","alias_value":"2602.07253v2","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.07253","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"pith_short_12","alias_value":"KFH6FBB6HHGK","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"pith_short_16","alias_value":"KFH6FBB6HHGKTAQE","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"pith_short_8","alias_value":"KFH6FBB6","created_at":"2026-06-01T01:02:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:KFH6FBB6HHGKTAQEOHQMYOCPGY","target":"record","payload":{"canonical_record":{"source":{"id":"2602.07253","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-02-06T23:05:48Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"7e8fa1d306afd600f28217644fa8940308becb3183c85a10ca69916a88b62c03","abstract_canon_sha256":"b74c620517faa4a0982038809784881c808697ce1e1bb0574d5c449481fce2f4"},"schema_version":"1.0"},"canonical_sha256":"514fe2843e39cca9820471e0cc384f3623785efe1f73d9c9229d925d2fa95d46","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:02:32.385272Z","signature_b64":"zRFYiyvKxVNVKkFbah7NqyqV8KwjfefkilYe+2X1B8F2vkqgePV30ZzSokzKso0YZaStl/ZlICOus99+UHJiBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"514fe2843e39cca9820471e0cc384f3623785efe1f73d9c9229d925d2fa95d46","last_reissued_at":"2026-06-01T01:02:32.384394Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:02:32.384394Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.07253","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":"2026-06-01T01:02:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2vQaG4+OBm0g7Mum2dFLaqE8x0ts+GMvgu2ouBR+saLB8KFapDz4FXJs91co+5ibQfTGyiWuJmmzBsTjbiW0BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T12:05:41.157367Z"},"content_sha256":"a09eacbe48cc8039e6af08b7cc85e5ae6de8433ef525cccc7539b3ff9d461c02","schema_version":"1.0","event_id":"sha256:a09eacbe48cc8039e6af08b7cc85e5ae6de8433ef525cccc7539b3ff9d461c02"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:KFH6FBB6HHGKTAQEOHQMYOCPGY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Out-of-Distribution Detection to Hallucination Detection: A Geometric View","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Litian Liu, Reza Pourreza, Roland Memisevic, Yao Qin, Yubing Jian","submitted_at":"2026-02-06T23:05:48Z","abstract_excerpt":"Detecting hallucinations in large language models is a critical open problem with significant implications for safety and reliability. While existing hallucination detection methods achieve strong performance in question-answering tasks, they remain less effective on tasks requiring reasoning. In this work, we revisit hallucination detection through the lens of out-of-distribution (OOD) detection, a well-studied problem in areas like computer vision. Treating next-token prediction in language models as a classification task allows us to apply OOD techniques, provided appropriate modifications "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.07253","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/2602.07253/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":"2026-06-01T01:02:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GW0KHU52+ch4+U452OuqhKx2PwTHm+MKjO4rOT8t/4SkhDN3ENIPjtHDlBS3qOwHJeZbT0bigOO6e6Hz7O7HAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T12:05:41.158017Z"},"content_sha256":"51d261cbb139e7c34c11222a1d99766ca6eac5928023d1c2e320206d350bb159","schema_version":"1.0","event_id":"sha256:51d261cbb139e7c34c11222a1d99766ca6eac5928023d1c2e320206d350bb159"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY/bundle.json","state_url":"https://pith.science/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY/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":"2026-06-03T12:05:41Z","links":{"resolver":"https://pith.science/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY","bundle":"https://pith.science/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY/bundle.json","state":"https://pith.science/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KFH6FBB6HHGKTAQEOHQMYOCPGY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:KFH6FBB6HHGKTAQEOHQMYOCPGY","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":"b74c620517faa4a0982038809784881c808697ce1e1bb0574d5c449481fce2f4","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-02-06T23:05:48Z","title_canon_sha256":"7e8fa1d306afd600f28217644fa8940308becb3183c85a10ca69916a88b62c03"},"schema_version":"1.0","source":{"id":"2602.07253","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.07253","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"arxiv_version","alias_value":"2602.07253v2","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.07253","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"pith_short_12","alias_value":"KFH6FBB6HHGK","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"pith_short_16","alias_value":"KFH6FBB6HHGKTAQE","created_at":"2026-06-01T01:02:32Z"},{"alias_kind":"pith_short_8","alias_value":"KFH6FBB6","created_at":"2026-06-01T01:02:32Z"}],"graph_snapshots":[{"event_id":"sha256:51d261cbb139e7c34c11222a1d99766ca6eac5928023d1c2e320206d350bb159","target":"graph","created_at":"2026-06-01T01:02:32Z","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/2602.07253/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Detecting hallucinations in large language models is a critical open problem with significant implications for safety and reliability. While existing hallucination detection methods achieve strong performance in question-answering tasks, they remain less effective on tasks requiring reasoning. In this work, we revisit hallucination detection through the lens of out-of-distribution (OOD) detection, a well-studied problem in areas like computer vision. Treating next-token prediction in language models as a classification task allows us to apply OOD techniques, provided appropriate modifications ","authors_text":"Litian Liu, Reza Pourreza, Roland Memisevic, Yao Qin, Yubing Jian","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-02-06T23:05:48Z","title":"From Out-of-Distribution Detection to Hallucination Detection: A Geometric View"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.07253","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:a09eacbe48cc8039e6af08b7cc85e5ae6de8433ef525cccc7539b3ff9d461c02","target":"record","created_at":"2026-06-01T01:02:32Z","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":"b74c620517faa4a0982038809784881c808697ce1e1bb0574d5c449481fce2f4","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-02-06T23:05:48Z","title_canon_sha256":"7e8fa1d306afd600f28217644fa8940308becb3183c85a10ca69916a88b62c03"},"schema_version":"1.0","source":{"id":"2602.07253","kind":"arxiv","version":2}},"canonical_sha256":"514fe2843e39cca9820471e0cc384f3623785efe1f73d9c9229d925d2fa95d46","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"514fe2843e39cca9820471e0cc384f3623785efe1f73d9c9229d925d2fa95d46","first_computed_at":"2026-06-01T01:02:32.384394Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:02:32.384394Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zRFYiyvKxVNVKkFbah7NqyqV8KwjfefkilYe+2X1B8F2vkqgePV30ZzSokzKso0YZaStl/ZlICOus99+UHJiBQ==","signature_status":"signed_v1","signed_at":"2026-06-01T01:02:32.385272Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.07253","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a09eacbe48cc8039e6af08b7cc85e5ae6de8433ef525cccc7539b3ff9d461c02","sha256:51d261cbb139e7c34c11222a1d99766ca6eac5928023d1c2e320206d350bb159"],"state_sha256":"94915326e7ed27a2999212498e8a5c4f1836fc51151f48f229592dc39d71e0c7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0ixOoUS5D9KE/EL595fj3uXQONkBrh54TC9I/QgawihNLkZT0pnnWtPO9cVSNPKrSE7tDz70G4NEu1zNfmaNCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T12:05:41.160218Z","bundle_sha256":"7aed6f055a4cb8356584106ae98fc718ae6cbf13ca1ddfe5a867bd62cc665fd0"}}