{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UNY6FLNGMQVPMFQRAWVKAJSP42","short_pith_number":"pith:UNY6FLNG","canonical_record":{"source":{"id":"2606.19351","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-27T12:20:28Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b6df4451516a3419b97174f340d33077493b61e855768a74303f4a253a765190","abstract_canon_sha256":"620a93cbca085065d39392db52cf7473d6584956eee4b01d58daabfe6e88bf34"},"schema_version":"1.0"},"canonical_sha256":"a371e2ada6642af6161105aaa0264fe69c1178e6164c5a7cca81ed4bcef06e27","source":{"kind":"arxiv","id":"2606.19351","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.19351","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"arxiv_version","alias_value":"2606.19351v1","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19351","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"pith_short_12","alias_value":"UNY6FLNGMQVP","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"pith_short_16","alias_value":"UNY6FLNGMQVPMFQR","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"pith_short_8","alias_value":"UNY6FLNG","created_at":"2026-06-19T16:12:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UNY6FLNGMQVPMFQRAWVKAJSP42","target":"record","payload":{"canonical_record":{"source":{"id":"2606.19351","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-27T12:20:28Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b6df4451516a3419b97174f340d33077493b61e855768a74303f4a253a765190","abstract_canon_sha256":"620a93cbca085065d39392db52cf7473d6584956eee4b01d58daabfe6e88bf34"},"schema_version":"1.0"},"canonical_sha256":"a371e2ada6642af6161105aaa0264fe69c1178e6164c5a7cca81ed4bcef06e27","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:12:22.936205Z","signature_b64":"oh2Zc2yXV2Rqhc+b41a1sqr2kW9zS+2eUCTqI4ZLaOTELWUhf3KgpDbTD7Rs8+n2Bx6OI+T85W4MWOMACuccCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a371e2ada6642af6161105aaa0264fe69c1178e6164c5a7cca81ed4bcef06e27","last_reissued_at":"2026-06-19T16:12:22.935867Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:12:22.935867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.19351","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-19T16:12:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tULTcYtEGl5Qv6IwSRAEBAuV6y5/RhcO9s3fTtAmoGFUeiHIaMasgCj1YoAZ5UyCXJ/ZMuZV2i7CCDmxDCVjCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T17:41:12.014430Z"},"content_sha256":"1309a9c134bd170a86d88f419d07223ea8e94d29a3238383a2110552c2512bfc","schema_version":"1.0","event_id":"sha256:1309a9c134bd170a86d88f419d07223ea8e94d29a3238383a2110552c2512bfc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UNY6FLNGMQVPMFQRAWVKAJSP42","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cheng Yang, Chuan Shi, Huadong Ma, Xinyan Zhu, Yaoqi Liu, Yue Gao","submitted_at":"2026-04-27T12:20:28Z","abstract_excerpt":"Knowledge graph (KG) reasoning infers new knowledge from existing facts and is widely applied in question answering, recommendation, and decision support. With the rapid development of large language models (LLMs), LLM-based KG reasoning frameworks have become increasingly popular by leveraging retrieved KG information. However, hallucinations in LLMs remain a critical issue. Even when relevant KG knowledge is incorporated, models may still generate incorrect outputs, leading to misinformation and unreliable decisions. Existing hallucination detection methods either focus on LLM internal state"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19351","kind":"arxiv","version":1},"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/2606.19351/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":"2026-06-19T16:12:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AYvAC02lHwCULAhX/ColsqISLP7OsqpS9Up/TVLQnqfhdv424xwFj3EoqYxRjd9YhFS6nBPW6TEQsownD4SmDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T17:41:12.014805Z"},"content_sha256":"4898221c83fe8fdff8607cb97a5a4681e3d28f99b181592fae52f8ca4bd67cba","schema_version":"1.0","event_id":"sha256:4898221c83fe8fdff8607cb97a5a4681e3d28f99b181592fae52f8ca4bd67cba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UNY6FLNGMQVPMFQRAWVKAJSP42/bundle.json","state_url":"https://pith.science/pith/UNY6FLNGMQVPMFQRAWVKAJSP42/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UNY6FLNGMQVPMFQRAWVKAJSP42/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":"2026-07-01T17:41:12Z","links":{"resolver":"https://pith.science/pith/UNY6FLNGMQVPMFQRAWVKAJSP42","bundle":"https://pith.science/pith/UNY6FLNGMQVPMFQRAWVKAJSP42/bundle.json","state":"https://pith.science/pith/UNY6FLNGMQVPMFQRAWVKAJSP42/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UNY6FLNGMQVPMFQRAWVKAJSP42/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UNY6FLNGMQVPMFQRAWVKAJSP42","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":"620a93cbca085065d39392db52cf7473d6584956eee4b01d58daabfe6e88bf34","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-27T12:20:28Z","title_canon_sha256":"b6df4451516a3419b97174f340d33077493b61e855768a74303f4a253a765190"},"schema_version":"1.0","source":{"id":"2606.19351","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.19351","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"arxiv_version","alias_value":"2606.19351v1","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19351","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"pith_short_12","alias_value":"UNY6FLNGMQVP","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"pith_short_16","alias_value":"UNY6FLNGMQVPMFQR","created_at":"2026-06-19T16:12:22Z"},{"alias_kind":"pith_short_8","alias_value":"UNY6FLNG","created_at":"2026-06-19T16:12:22Z"}],"graph_snapshots":[{"event_id":"sha256:4898221c83fe8fdff8607cb97a5a4681e3d28f99b181592fae52f8ca4bd67cba","target":"graph","created_at":"2026-06-19T16:12:22Z","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/2606.19351/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge graph (KG) reasoning infers new knowledge from existing facts and is widely applied in question answering, recommendation, and decision support. With the rapid development of large language models (LLMs), LLM-based KG reasoning frameworks have become increasingly popular by leveraging retrieved KG information. However, hallucinations in LLMs remain a critical issue. Even when relevant KG knowledge is incorporated, models may still generate incorrect outputs, leading to misinformation and unreliable decisions. Existing hallucination detection methods either focus on LLM internal state","authors_text":"Cheng Yang, Chuan Shi, Huadong Ma, Xinyan Zhu, Yaoqi Liu, Yue Gao","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-27T12:20:28Z","title":"Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19351","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":"sha256:1309a9c134bd170a86d88f419d07223ea8e94d29a3238383a2110552c2512bfc","target":"record","created_at":"2026-06-19T16:12:22Z","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":"620a93cbca085065d39392db52cf7473d6584956eee4b01d58daabfe6e88bf34","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-04-27T12:20:28Z","title_canon_sha256":"b6df4451516a3419b97174f340d33077493b61e855768a74303f4a253a765190"},"schema_version":"1.0","source":{"id":"2606.19351","kind":"arxiv","version":1}},"canonical_sha256":"a371e2ada6642af6161105aaa0264fe69c1178e6164c5a7cca81ed4bcef06e27","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a371e2ada6642af6161105aaa0264fe69c1178e6164c5a7cca81ed4bcef06e27","first_computed_at":"2026-06-19T16:12:22.935867Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:12:22.935867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oh2Zc2yXV2Rqhc+b41a1sqr2kW9zS+2eUCTqI4ZLaOTELWUhf3KgpDbTD7Rs8+n2Bx6OI+T85W4MWOMACuccCQ==","signature_status":"signed_v1","signed_at":"2026-06-19T16:12:22.936205Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.19351","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1309a9c134bd170a86d88f419d07223ea8e94d29a3238383a2110552c2512bfc","sha256:4898221c83fe8fdff8607cb97a5a4681e3d28f99b181592fae52f8ca4bd67cba"],"state_sha256":"ea314a01230166d92e311b711ab2e5dcff06f4fab86297390b70c7ff92d1a2a7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"intjMHg5cx8ogbXELcGleBZp10rTMm7nW7kDKfAsDjeP3d8xUtAH/QI8k+nVUHGVtVHp/rgCFuGqOVo9JHDTDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T17:41:12.016851Z","bundle_sha256":"5b678658f6fe800173cc28aed7a89057da0332b8a44f9cc4944d8578641c1b4c"}}