{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:YANBCOK3XN4NWF657RR5MJ4NZV","short_pith_number":"pith:YANBCOK3","canonical_record":{"source":{"id":"2312.02783","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-12-05T14:14:27Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2db24a74fd950d3f69084cb8e66197a0b0d6235075e93fe76fd929a83a0d6cac","abstract_canon_sha256":"2733ed255ff27101a285b6145e3a74484f23634f4053a676cb4edbf02f692cfc"},"schema_version":"1.0"},"canonical_sha256":"c01a11395bbb78db17ddfc63d6278dcd528e86f1528c94d899461310b37876be","source":{"kind":"arxiv","id":"2312.02783","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02783","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02783v4","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02783","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"pith_short_12","alias_value":"YANBCOK3XN4N","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"pith_short_16","alias_value":"YANBCOK3XN4NWF65","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"pith_short_8","alias_value":"YANBCOK3","created_at":"2026-07-05T09:38:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:YANBCOK3XN4NWF657RR5MJ4NZV","target":"record","payload":{"canonical_record":{"source":{"id":"2312.02783","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-12-05T14:14:27Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2db24a74fd950d3f69084cb8e66197a0b0d6235075e93fe76fd929a83a0d6cac","abstract_canon_sha256":"2733ed255ff27101a285b6145e3a74484f23634f4053a676cb4edbf02f692cfc"},"schema_version":"1.0"},"canonical_sha256":"c01a11395bbb78db17ddfc63d6278dcd528e86f1528c94d899461310b37876be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:38:22.938963Z","signature_b64":"gKE2XRSpHvLBgvmSP9t4u8a1iFttuipgfL7iUVRgADNUGiyQrYTdRoPLyMlVIe7etnbkykUC1es2Xml26ByBBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c01a11395bbb78db17ddfc63d6278dcd528e86f1528c94d899461310b37876be","last_reissued_at":"2026-07-05T09:38:22.938452Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:38:22.938452Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.02783","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tjKjuGcIxudUB8UnIoAQsAhAaQ8IGVSvK685Wr9G5i6n1lA8g1/A1S0AY+fi7aN7+MRtw8E4ZpyImgsEHZJ/Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:48:17.678506Z"},"content_sha256":"21b5389a42596964cd0d2b67f4aa813c5850b31b55143467ef62b2c7ba879653","schema_version":"1.0","event_id":"sha256:21b5389a42596964cd0d2b67f4aa813c5850b31b55143467ef62b2c7ba879653"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:YANBCOK3XN4NWF657RR5MJ4NZV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large Language Models on Graphs: A Comprehensive Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Bowen Jin, Chi Han, Gang Liu, Heng Ji, Jiawei Han, Meng Jiang","submitted_at":"2023-12-05T14:14:27Z","abstract_excerpt":"Large language models (LLMs), such as GPT4 and LLaMA, are creating significant advancements in natural language processing, due to their strong text encoding/decoding ability and newly found emergent capability (e.g., reasoning). While LLMs are mainly designed to process pure texts, there are many real-world scenarios where text data is associated with rich structure information in the form of graphs (e.g., academic networks, and e-commerce networks) or scenarios where graph data is paired with rich textual information (e.g., molecules with descriptions). Besides, although LLMs have shown thei"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02783","kind":"arxiv","version":4},"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/2312.02783/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":"2026-07-05T09:38:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N5Q+lnjvUmVdjNZy/JFO0QMmOEkx9eJqjmSFfzLZXufp/KLdU/Ksl9b+EmKXCWVBFjao3nSCdCnBfPV6DespDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:48:17.679010Z"},"content_sha256":"68df2b45e948b12add9471cc161f5f0539a09b6073fa7960cdfd8f20b1f6724d","schema_version":"1.0","event_id":"sha256:68df2b45e948b12add9471cc161f5f0539a09b6073fa7960cdfd8f20b1f6724d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YANBCOK3XN4NWF657RR5MJ4NZV/bundle.json","state_url":"https://pith.science/pith/YANBCOK3XN4NWF657RR5MJ4NZV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YANBCOK3XN4NWF657RR5MJ4NZV/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":"2026-08-09T22:48:17Z","links":{"resolver":"https://pith.science/pith/YANBCOK3XN4NWF657RR5MJ4NZV","bundle":"https://pith.science/pith/YANBCOK3XN4NWF657RR5MJ4NZV/bundle.json","state":"https://pith.science/pith/YANBCOK3XN4NWF657RR5MJ4NZV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YANBCOK3XN4NWF657RR5MJ4NZV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YANBCOK3XN4NWF657RR5MJ4NZV","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":"2733ed255ff27101a285b6145e3a74484f23634f4053a676cb4edbf02f692cfc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-12-05T14:14:27Z","title_canon_sha256":"2db24a74fd950d3f69084cb8e66197a0b0d6235075e93fe76fd929a83a0d6cac"},"schema_version":"1.0","source":{"id":"2312.02783","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02783","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02783v4","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02783","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"pith_short_12","alias_value":"YANBCOK3XN4N","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"pith_short_16","alias_value":"YANBCOK3XN4NWF65","created_at":"2026-07-05T09:38:22Z"},{"alias_kind":"pith_short_8","alias_value":"YANBCOK3","created_at":"2026-07-05T09:38:22Z"}],"graph_snapshots":[{"event_id":"sha256:68df2b45e948b12add9471cc161f5f0539a09b6073fa7960cdfd8f20b1f6724d","target":"graph","created_at":"2026-07-05T09:38:22Z","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/2312.02783/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs), such as GPT4 and LLaMA, are creating significant advancements in natural language processing, due to their strong text encoding/decoding ability and newly found emergent capability (e.g., reasoning). While LLMs are mainly designed to process pure texts, there are many real-world scenarios where text data is associated with rich structure information in the form of graphs (e.g., academic networks, and e-commerce networks) or scenarios where graph data is paired with rich textual information (e.g., molecules with descriptions). Besides, although LLMs have shown thei","authors_text":"Bowen Jin, Chi Han, Gang Liu, Heng Ji, Jiawei Han, Meng Jiang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-12-05T14:14:27Z","title":"Large Language Models on Graphs: A Comprehensive Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02783","kind":"arxiv","version":4},"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":"sha256:21b5389a42596964cd0d2b67f4aa813c5850b31b55143467ef62b2c7ba879653","target":"record","created_at":"2026-07-05T09:38:22Z","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":"2733ed255ff27101a285b6145e3a74484f23634f4053a676cb4edbf02f692cfc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-12-05T14:14:27Z","title_canon_sha256":"2db24a74fd950d3f69084cb8e66197a0b0d6235075e93fe76fd929a83a0d6cac"},"schema_version":"1.0","source":{"id":"2312.02783","kind":"arxiv","version":4}},"canonical_sha256":"c01a11395bbb78db17ddfc63d6278dcd528e86f1528c94d899461310b37876be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c01a11395bbb78db17ddfc63d6278dcd528e86f1528c94d899461310b37876be","first_computed_at":"2026-07-05T09:38:22.938452Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:38:22.938452Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gKE2XRSpHvLBgvmSP9t4u8a1iFttuipgfL7iUVRgADNUGiyQrYTdRoPLyMlVIe7etnbkykUC1es2Xml26ByBBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:38:22.938963Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.02783","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:21b5389a42596964cd0d2b67f4aa813c5850b31b55143467ef62b2c7ba879653","sha256:68df2b45e948b12add9471cc161f5f0539a09b6073fa7960cdfd8f20b1f6724d"],"state_sha256":"68aac868f624797c65182b00237fa17d3430cd7c6a94a591359b6153eb6049fd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I2xUlaQnvH5yszDT8+RadkBL1vEWreyzznVLRckS6QXPcbi2hqMOT+G8qSMbwxfg1QXLeN1GS6wq7sG9BtSYDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T22:48:17.684127Z","bundle_sha256":"55ec005da531869b301505dfd9f2464e67ffe48d8c0db671ba4426aebc711774"}}