{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:IYETJCWKROV3S72ZU5KEHK4XAG","short_pith_number":"pith:IYETJCWK","canonical_record":{"source":{"id":"2305.15066","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-05-24T11:53:19Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"e3730f220312210a7d160d05d0bae8bfd3644e6b8539e201079e475c9ffe0a4d","abstract_canon_sha256":"94e72309cac524fcf545147517a8a285d1f5aa9c1e3b62e7a0cc1f30d78bf66c"},"schema_version":"1.0"},"canonical_sha256":"4609348aca8babb97f59a75443ab970185c5696af752a580f17f181c9ac4f0f7","source":{"kind":"arxiv","id":"2305.15066","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15066","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15066v2","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15066","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"pith_short_12","alias_value":"IYETJCWKROV3","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"IYETJCWKROV3S72Z","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"IYETJCWK","created_at":"2026-07-05T06:29:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:IYETJCWKROV3S72ZU5KEHK4XAG","target":"record","payload":{"canonical_record":{"source":{"id":"2305.15066","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-05-24T11:53:19Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"e3730f220312210a7d160d05d0bae8bfd3644e6b8539e201079e475c9ffe0a4d","abstract_canon_sha256":"94e72309cac524fcf545147517a8a285d1f5aa9c1e3b62e7a0cc1f30d78bf66c"},"schema_version":"1.0"},"canonical_sha256":"4609348aca8babb97f59a75443ab970185c5696af752a580f17f181c9ac4f0f7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:29:50.622953Z","signature_b64":"3DCkO8Y1PCVQY1bog7hnv4F8+kAX3LTdlVwZ7AcHJfse0kaV7cq6zrheW+T11jHZj6rK4sKWh98TVIr5Y5d6BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4609348aca8babb97f59a75443ab970185c5696af752a580f17f181c9ac4f0f7","last_reissued_at":"2026-07-05T06:29:50.622433Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:29:50.622433Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.15066","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":"2026-07-05T06:29:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BVfcA8Jfoqki00MArQ7PohtON4qF8LKF/mA9Iqdlol68FKFtXikdrcK4Cq9VgZuX60W6tk4YQpwXs/E/FxChCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:12:22.347487Z"},"content_sha256":"6effedbaa3a4828a7055b1a34239ec84018e4e7b0d0221611a781c5e0bb5c5e3","schema_version":"1.0","event_id":"sha256:6effedbaa3a4828a7055b1a34239ec84018e4e7b0d0221611a781c5e0bb5c5e3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:IYETJCWKROV3S72ZU5KEHK4XAG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Hengyu Liu, Jiayan Guo, Lun Du, Mengyu Zhou, Shi Han, Xinyi He","submitted_at":"2023-05-24T11:53:19Z","abstract_excerpt":"Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language processing tasks. In the real world, graph data is ubiquitous and an essential part of AGI and prevails in domains like social network analysis, bioinformatics and recommender systems. The training corpus of large language models often includes some algorithmic components, which allows them to achieve certain effects on some graph data-related problems. However, there is still little research on their performance on a broad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15066","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/2305.15066/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":"2026-07-05T06:29:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"meVRsSMw7ymUYSzdlhyE1JQA+NIRaKkxFQjXDeaqphzG3T8Lo8ATDGWV0QPPQeUrXrVqklh9obxH1UO4vqeoAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:12:22.347978Z"},"content_sha256":"ddc31b21c1ca5858a33ffc77148a1707aaae6c2bd696f87fcec503811292b3ee","schema_version":"1.0","event_id":"sha256:ddc31b21c1ca5858a33ffc77148a1707aaae6c2bd696f87fcec503811292b3ee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IYETJCWKROV3S72ZU5KEHK4XAG/bundle.json","state_url":"https://pith.science/pith/IYETJCWKROV3S72ZU5KEHK4XAG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IYETJCWKROV3S72ZU5KEHK4XAG/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":"2026-08-23T22:12:22Z","links":{"resolver":"https://pith.science/pith/IYETJCWKROV3S72ZU5KEHK4XAG","bundle":"https://pith.science/pith/IYETJCWKROV3S72ZU5KEHK4XAG/bundle.json","state":"https://pith.science/pith/IYETJCWKROV3S72ZU5KEHK4XAG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IYETJCWKROV3S72ZU5KEHK4XAG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IYETJCWKROV3S72ZU5KEHK4XAG","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":"94e72309cac524fcf545147517a8a285d1f5aa9c1e3b62e7a0cc1f30d78bf66c","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-05-24T11:53:19Z","title_canon_sha256":"e3730f220312210a7d160d05d0bae8bfd3644e6b8539e201079e475c9ffe0a4d"},"schema_version":"1.0","source":{"id":"2305.15066","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15066","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15066v2","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15066","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"pith_short_12","alias_value":"IYETJCWKROV3","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"IYETJCWKROV3S72Z","created_at":"2026-07-05T06:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"IYETJCWK","created_at":"2026-07-05T06:29:50Z"}],"graph_snapshots":[{"event_id":"sha256:ddc31b21c1ca5858a33ffc77148a1707aaae6c2bd696f87fcec503811292b3ee","target":"graph","created_at":"2026-07-05T06:29:50Z","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/2305.15066/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language processing tasks. In the real world, graph data is ubiquitous and an essential part of AGI and prevails in domains like social network analysis, bioinformatics and recommender systems. The training corpus of large language models often includes some algorithmic components, which allows them to achieve certain effects on some graph data-related problems. However, there is still little research on their performance on a broad","authors_text":"Hengyu Liu, Jiayan Guo, Lun Du, Mengyu Zhou, Shi Han, Xinyi He","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-05-24T11:53:19Z","title":"GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15066","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":"sha256:6effedbaa3a4828a7055b1a34239ec84018e4e7b0d0221611a781c5e0bb5c5e3","target":"record","created_at":"2026-07-05T06:29:50Z","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":"94e72309cac524fcf545147517a8a285d1f5aa9c1e3b62e7a0cc1f30d78bf66c","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-05-24T11:53:19Z","title_canon_sha256":"e3730f220312210a7d160d05d0bae8bfd3644e6b8539e201079e475c9ffe0a4d"},"schema_version":"1.0","source":{"id":"2305.15066","kind":"arxiv","version":2}},"canonical_sha256":"4609348aca8babb97f59a75443ab970185c5696af752a580f17f181c9ac4f0f7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4609348aca8babb97f59a75443ab970185c5696af752a580f17f181c9ac4f0f7","first_computed_at":"2026-07-05T06:29:50.622433Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:29:50.622433Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3DCkO8Y1PCVQY1bog7hnv4F8+kAX3LTdlVwZ7AcHJfse0kaV7cq6zrheW+T11jHZj6rK4sKWh98TVIr5Y5d6BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:29:50.622953Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.15066","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6effedbaa3a4828a7055b1a34239ec84018e4e7b0d0221611a781c5e0bb5c5e3","sha256:ddc31b21c1ca5858a33ffc77148a1707aaae6c2bd696f87fcec503811292b3ee"],"state_sha256":"0b7a5100cf0da76bd35c7f8417dec2ea3113736e8f089c950d03cc1756718e45"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0/LCj/7VdXpGSwdcq1cQ3AHITOM+h9GE7Ztktupwaz3FJ8CQUSWVNQ6SDEkH4UIYFgUA4egEfuUkObzO6MEkCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T22:12:22.352399Z","bundle_sha256":"2795e7124957588e15315ca90266e1fb428b7cb701f819d86927cdc2c9ea8452"}}