{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3AY47LPXOLN4JKEH4O3L22KPN7","short_pith_number":"pith:3AY47LPX","canonical_record":{"source":{"id":"2507.19526","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-20T09:18:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"29a47c6a6a68bfa64b2b0ed28a15a1f2dc2e7f2eabc31147f209e6fe174b101a","abstract_canon_sha256":"29fd72456c72ee90808d9f7684d41870bee1f7b98b4a29ea649f373206f75a90"},"schema_version":"1.0"},"canonical_sha256":"d831cfadf772dbc4a887e3b6bd694f6fd323a519614c9a91beb9070543a98fe3","source":{"kind":"arxiv","id":"2507.19526","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.19526","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"arxiv_version","alias_value":"2507.19526v1","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.19526","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"pith_short_12","alias_value":"3AY47LPXOLN4","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"pith_short_16","alias_value":"3AY47LPXOLN4JKEH","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"pith_short_8","alias_value":"3AY47LPX","created_at":"2026-07-05T11:43:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3AY47LPXOLN4JKEH4O3L22KPN7","target":"record","payload":{"canonical_record":{"source":{"id":"2507.19526","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-20T09:18:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"29a47c6a6a68bfa64b2b0ed28a15a1f2dc2e7f2eabc31147f209e6fe174b101a","abstract_canon_sha256":"29fd72456c72ee90808d9f7684d41870bee1f7b98b4a29ea649f373206f75a90"},"schema_version":"1.0"},"canonical_sha256":"d831cfadf772dbc4a887e3b6bd694f6fd323a519614c9a91beb9070543a98fe3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:35.848118Z","signature_b64":"PV+BcSRxtevMvIojQ9EwnPhbUOulKF74JRWhXkoNqsL34+IICNxSBo2iIISRsqmm5AzN9sPz27lDGUYX2++CDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d831cfadf772dbc4a887e3b6bd694f6fd323a519614c9a91beb9070543a98fe3","last_reissued_at":"2026-07-05T11:43:35.847686Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:35.847686Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.19526","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":"2026-07-05T11:43:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N7ULRm1HOMJTOf68ikHQ19ER7nYfESo3XHWDUeKSJlRR5wHvbCz4MzZqvSLrxDSQLu1OSY6/LQtFaKpmOjDbAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:12:21.273543Z"},"content_sha256":"7facb456b97cb2ba530266c29fd952baa61174cd1760826490716b462991e6eb","schema_version":"1.0","event_id":"sha256:7facb456b97cb2ba530266c29fd952baa61174cd1760826490716b462991e6eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3AY47LPXOLN4JKEH4O3L22KPN7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quantizing Text-attributed Graphs for Semantic-Structural Integration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Hao Wu, Jianyuan Bo, Yuan Fang","submitted_at":"2025-07-20T09:18:02Z","abstract_excerpt":"Text-attributed graphs (TAGs) have emerged as a powerful representation for modeling complex relationships across diverse domains. With the rise of large language models (LLMs), there is growing interest in leveraging their capabilities for graph learning. However, current approaches face significant challenges in embedding structural information into LLM-compatible formats, requiring either computationally expensive alignment mechanisms or manual graph verbalization techniques that often lose critical structural details. Moreover, these methods typically require labeled data from source domai"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.19526","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/2507.19526/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":"2026-07-05T11:43:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XFsO0QQU+l9emgXXFkMB7TKyX9I9yPP3YXkrfPDJpsaeJ3i2acesxplo7ajKySgC0h36v9Tcz3P1fbjV3pqjBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:12:21.273956Z"},"content_sha256":"45cb78d692ffe829ce06396dd3b92fbbbe9cbf8768eea86703cc5c16465fba9d","schema_version":"1.0","event_id":"sha256:45cb78d692ffe829ce06396dd3b92fbbbe9cbf8768eea86703cc5c16465fba9d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3AY47LPXOLN4JKEH4O3L22KPN7/bundle.json","state_url":"https://pith.science/pith/3AY47LPXOLN4JKEH4O3L22KPN7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3AY47LPXOLN4JKEH4O3L22KPN7/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":"2026-08-05T23:12:21Z","links":{"resolver":"https://pith.science/pith/3AY47LPXOLN4JKEH4O3L22KPN7","bundle":"https://pith.science/pith/3AY47LPXOLN4JKEH4O3L22KPN7/bundle.json","state":"https://pith.science/pith/3AY47LPXOLN4JKEH4O3L22KPN7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3AY47LPXOLN4JKEH4O3L22KPN7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3AY47LPXOLN4JKEH4O3L22KPN7","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":"29fd72456c72ee90808d9f7684d41870bee1f7b98b4a29ea649f373206f75a90","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-20T09:18:02Z","title_canon_sha256":"29a47c6a6a68bfa64b2b0ed28a15a1f2dc2e7f2eabc31147f209e6fe174b101a"},"schema_version":"1.0","source":{"id":"2507.19526","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.19526","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"arxiv_version","alias_value":"2507.19526v1","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.19526","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"pith_short_12","alias_value":"3AY47LPXOLN4","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"pith_short_16","alias_value":"3AY47LPXOLN4JKEH","created_at":"2026-07-05T11:43:35Z"},{"alias_kind":"pith_short_8","alias_value":"3AY47LPX","created_at":"2026-07-05T11:43:35Z"}],"graph_snapshots":[{"event_id":"sha256:45cb78d692ffe829ce06396dd3b92fbbbe9cbf8768eea86703cc5c16465fba9d","target":"graph","created_at":"2026-07-05T11:43:35Z","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/2507.19526/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-attributed graphs (TAGs) have emerged as a powerful representation for modeling complex relationships across diverse domains. With the rise of large language models (LLMs), there is growing interest in leveraging their capabilities for graph learning. However, current approaches face significant challenges in embedding structural information into LLM-compatible formats, requiring either computationally expensive alignment mechanisms or manual graph verbalization techniques that often lose critical structural details. Moreover, these methods typically require labeled data from source domai","authors_text":"Hao Wu, Jianyuan Bo, Yuan Fang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-20T09:18:02Z","title":"Quantizing Text-attributed Graphs for Semantic-Structural Integration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.19526","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":"sha256:7facb456b97cb2ba530266c29fd952baa61174cd1760826490716b462991e6eb","target":"record","created_at":"2026-07-05T11:43:35Z","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":"29fd72456c72ee90808d9f7684d41870bee1f7b98b4a29ea649f373206f75a90","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-07-20T09:18:02Z","title_canon_sha256":"29a47c6a6a68bfa64b2b0ed28a15a1f2dc2e7f2eabc31147f209e6fe174b101a"},"schema_version":"1.0","source":{"id":"2507.19526","kind":"arxiv","version":1}},"canonical_sha256":"d831cfadf772dbc4a887e3b6bd694f6fd323a519614c9a91beb9070543a98fe3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d831cfadf772dbc4a887e3b6bd694f6fd323a519614c9a91beb9070543a98fe3","first_computed_at":"2026-07-05T11:43:35.847686Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:43:35.847686Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PV+BcSRxtevMvIojQ9EwnPhbUOulKF74JRWhXkoNqsL34+IICNxSBo2iIISRsqmm5AzN9sPz27lDGUYX2++CDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:43:35.848118Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.19526","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7facb456b97cb2ba530266c29fd952baa61174cd1760826490716b462991e6eb","sha256:45cb78d692ffe829ce06396dd3b92fbbbe9cbf8768eea86703cc5c16465fba9d"],"state_sha256":"284a3fbf32487d19e91a8ecd533f9b6ecf0bf2719e505456869541513322dc4b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d9oVMh7OFdc1swwHqc88l/f/KjsLEG3V7xkO2IGkTzTdeEOGJ43ul2cAccf1p/+ZYHA8WuZYWuxs2c0l4Au/Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T23:12:21.276893Z","bundle_sha256":"2cd7710352aecb7db0e73830840f449eb552c8c5795113e4a98e6248741a9e85"}}