{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:KVTIRZWVFMQVCOERWVOFAG3EOR","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":"8d90a43edc321c77165274d34a3db7b2aa691e954ec170da0bdec38f76faf07f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-01T13:02:47Z","title_canon_sha256":"99041fa9236cf0a935ec249983096b08f021432aaa96f5d84b900ebf6c5abb20"},"schema_version":"1.0","source":{"id":"2503.00476","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.00476","created_at":"2026-07-05T10:22:23Z"},{"alias_kind":"arxiv_version","alias_value":"2503.00476v1","created_at":"2026-07-05T10:22:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.00476","created_at":"2026-07-05T10:22:23Z"},{"alias_kind":"pith_short_12","alias_value":"KVTIRZWVFMQV","created_at":"2026-07-05T10:22:23Z"},{"alias_kind":"pith_short_16","alias_value":"KVTIRZWVFMQVCOER","created_at":"2026-07-05T10:22:23Z"},{"alias_kind":"pith_short_8","alias_value":"KVTIRZWV","created_at":"2026-07-05T10:22:23Z"}],"graph_snapshots":[{"event_id":"sha256:948c311bc686dc341393a69c419f712d4c3cab605a3552e6f181adfbe1ce156b","target":"graph","created_at":"2026-07-05T10:22:23Z","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/2503.00476/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) have achieved significant success in machine learning, with wide applications in social networks, bioinformatics, knowledge graphs, and other fields. Most research assumes ideal closed-set environments. However, in real-world open-set environments, graph learning models face challenges in robustness and reliability due to unseen classes. This highlights the need for Graph Open-Set Recognition (GOSR) methods to address these issues and ensure effective GNN application in practical scenarios. Research in GOSR is in its early stages, with a lack of a comprehensive ben","authors_text":"Guangyao Chen, Jieming Shi, Rundong He, Wentao Zhang, Yicong Dong, Yilong Yin, Zhongyi Han","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-01T13:02:47Z","title":"G-OSR: A Comprehensive Benchmark for Graph Open-Set Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.00476","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:b7cb69dd4694257265121d4c4a511e0300f9c6d939e40f2a28b6963a1d896154","target":"record","created_at":"2026-07-05T10:22:23Z","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":"8d90a43edc321c77165274d34a3db7b2aa691e954ec170da0bdec38f76faf07f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-01T13:02:47Z","title_canon_sha256":"99041fa9236cf0a935ec249983096b08f021432aaa96f5d84b900ebf6c5abb20"},"schema_version":"1.0","source":{"id":"2503.00476","kind":"arxiv","version":1}},"canonical_sha256":"556688e6d52b21513891b55c501b64747a952f797c90aecfc9c5704078d86c9f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"556688e6d52b21513891b55c501b64747a952f797c90aecfc9c5704078d86c9f","first_computed_at":"2026-07-05T10:22:23.637915Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:22:23.637915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SlYuPp0Fcqft/kmEbBbQq+fN/4U4jiXSoVA0q//zJFplx65S+HFQaNYa/j4ZFzS/WSaTBSqoeANCx0p0yepYBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:22:23.638372Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.00476","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b7cb69dd4694257265121d4c4a511e0300f9c6d939e40f2a28b6963a1d896154","sha256:948c311bc686dc341393a69c419f712d4c3cab605a3552e6f181adfbe1ce156b"],"state_sha256":"13059fef3e66589a74d595864308c4d01a68b6bc6a99d8675091ae6de54d6ad4"}