{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GHPU2W5EPL4CAD5I2T7CAHDDET","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":"9f74fc6e4448347b368308c1131c3ee7b0f731caadfb233579a79f742eebd479","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-09-29T04:05:48Z","title_canon_sha256":"02bafa974516e8fb9581a6735a26e97b996246bb6d9545e4c7210d98a5b9524c"},"schema_version":"1.0","source":{"id":"2509.24256","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.24256","created_at":"2026-07-14T01:22:01Z"},{"alias_kind":"arxiv_version","alias_value":"2509.24256v2","created_at":"2026-07-14T01:22:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.24256","created_at":"2026-07-14T01:22:01Z"},{"alias_kind":"pith_short_12","alias_value":"GHPU2W5EPL4C","created_at":"2026-07-14T01:22:01Z"},{"alias_kind":"pith_short_16","alias_value":"GHPU2W5EPL4CAD5I","created_at":"2026-07-14T01:22:01Z"},{"alias_kind":"pith_short_8","alias_value":"GHPU2W5E","created_at":"2026-07-14T01:22:01Z"}],"graph_snapshots":[{"event_id":"sha256:716c5aba2c5ca511f9510f17e6e12fac91c1d9a96d6eb1b5ac5cd70a5629af2d","target":"graph","created_at":"2026-07-14T01:22:01Z","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/2509.24256/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The pretrain-transfer paradigm, which underpins the success of large language models (LLMs), has demonstrated the immense power of creating foundation models that learn generalizable representations from vast datasets. However, extending this paradigm to Operations Research (OR) problems on graph structures remains challenging due to the fundamental conflict between the statistical flexibility of language and the strict combinatorial constraints of graphs. To bridge this gap, we introduce the Graph Foundation Model (GFM), the first framework capable of solving all distance-based optimization p","authors_text":"Jingyuan Yang, Pujun Zhang, Shaochong Lin, Yuan Qu, Yunhao Liang, Zuo-Jun Max Shen","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-09-29T04:05:48Z","title":"Graph Optimization Foundation Model: Tokenizing Graph via A Language-Model Paradigm"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.24256","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":"sha256:1ca70b63ae27123d786b2c011c4ea835d3ab57d9bdadc2c6d31f53c2bb5c70a8","target":"record","created_at":"2026-07-14T01:22:01Z","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":"9f74fc6e4448347b368308c1131c3ee7b0f731caadfb233579a79f742eebd479","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-09-29T04:05:48Z","title_canon_sha256":"02bafa974516e8fb9581a6735a26e97b996246bb6d9545e4c7210d98a5b9524c"},"schema_version":"1.0","source":{"id":"2509.24256","kind":"arxiv","version":2}},"canonical_sha256":"31df4d5ba47af8200fa8d4fe201c6324cb00a3beb4c1c2a1409128e2e559c085","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"31df4d5ba47af8200fa8d4fe201c6324cb00a3beb4c1c2a1409128e2e559c085","first_computed_at":"2026-07-14T01:22:01.148557Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T01:22:01.148557Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PcFpKq8hqGQ/Iq4FRSjvgL/HrgrL0ZeBMOKHeR0e9Zbcz5Dhk4sji+HHNV3ITF+aVaYDl4++kASi3ObSyfrnBQ==","signature_status":"signed_v1","signed_at":"2026-07-14T01:22:01.149434Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.24256","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ca70b63ae27123d786b2c011c4ea835d3ab57d9bdadc2c6d31f53c2bb5c70a8","sha256:716c5aba2c5ca511f9510f17e6e12fac91c1d9a96d6eb1b5ac5cd70a5629af2d"],"state_sha256":"951f1ee92d7019a95b408cb15ac11b499e5e17912340617b03c6522a098a1c6f"}