{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2IOE5Y2LULGUMLJFP3SHBULPPW","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":"9056d724fda70c0083e77f19eefbeae11039d914f452f589e8d3cafb63a7d45f","cross_cats_sorted":["cs.GT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-23T20:35:03Z","title_canon_sha256":"98acf7addd2b16d2402d279ed4658f67ec19c9378ce14460fbbf6de30841f1c8"},"schema_version":"1.0","source":{"id":"2503.18195","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18195","created_at":"2026-07-05T10:38:04Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18195v1","created_at":"2026-07-05T10:38:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18195","created_at":"2026-07-05T10:38:04Z"},{"alias_kind":"pith_short_12","alias_value":"2IOE5Y2LULGU","created_at":"2026-07-05T10:38:04Z"},{"alias_kind":"pith_short_16","alias_value":"2IOE5Y2LULGUMLJF","created_at":"2026-07-05T10:38:04Z"},{"alias_kind":"pith_short_8","alias_value":"2IOE5Y2L","created_at":"2026-07-05T10:38:04Z"}],"graph_snapshots":[{"event_id":"sha256:57ae76e5dad6c5322e01b0f9df7765c5cdd99f3c94363fc26ead72a0ee224b87","target":"graph","created_at":"2026-07-05T10:38:04Z","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/2503.18195/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) have demonstrated remarkable performance in various graph-based machine learning tasks, yet evaluating the importance of neighbors of testing nodes remains largely unexplored due to the challenge of assessing data importance without test labels. To address this gap, we propose Shapley-Guided Utility Learning (SGUL), a novel framework for graph inference data valuation. SGUL innovatively combines transferable data-specific and modelspecific features to approximate test accuracy without relying on ground truth labels. By incorporating Shapley values as a preprocessin","authors_text":"Hongliang Chi, Qiong Wu, Yao Ma, Zhengyi Zhou","cross_cats":["cs.GT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-23T20:35:03Z","title":"Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18195","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":"sha256:9787bc4f9bca7c1effe61e170c6c70607d2420e3fb2b27b4e63f2566ab9bdf2a","target":"record","created_at":"2026-07-05T10:38:04Z","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":"9056d724fda70c0083e77f19eefbeae11039d914f452f589e8d3cafb63a7d45f","cross_cats_sorted":["cs.GT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-23T20:35:03Z","title_canon_sha256":"98acf7addd2b16d2402d279ed4658f67ec19c9378ce14460fbbf6de30841f1c8"},"schema_version":"1.0","source":{"id":"2503.18195","kind":"arxiv","version":1}},"canonical_sha256":"d21c4ee34ba2cd462d257ee470d16f7d80789fd91e0c45bb34cf440d6c7c0037","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d21c4ee34ba2cd462d257ee470d16f7d80789fd91e0c45bb34cf440d6c7c0037","first_computed_at":"2026-07-05T10:38:04.861058Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:38:04.861058Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JxhJUWMQgZrHy7ddKeSTF41qkoFZGe87X2Ly8xw6CIw7cUpGrqYnQlOXGucA3f/fwMyhOX/46URLlxycr2JLAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:38:04.861916Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.18195","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9787bc4f9bca7c1effe61e170c6c70607d2420e3fb2b27b4e63f2566ab9bdf2a","sha256:57ae76e5dad6c5322e01b0f9df7765c5cdd99f3c94363fc26ead72a0ee224b87"],"state_sha256":"09a6f4d84d45adf4c254b7e4f1f57970711719ecc96512d247d8d0d6ecb06d40"}