{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:K4WZPF5OEAMPPYY5JI3DB4PXGS","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":"b0abe2f79720b83c0bc421c597684ec872ff7955a3462c6cbf5d48254462a149","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-19T14:59:12Z","title_canon_sha256":"3ddaadc0b451bae6b41c0e38864446df0c3b15c1113ffeec25fc0da10d4662c0"},"schema_version":"1.0","source":{"id":"2607.17281","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.17281","created_at":"2026-07-21T01:21:25Z"},{"alias_kind":"arxiv_version","alias_value":"2607.17281v1","created_at":"2026-07-21T01:21:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.17281","created_at":"2026-07-21T01:21:25Z"},{"alias_kind":"pith_short_12","alias_value":"K4WZPF5OEAMP","created_at":"2026-07-21T01:21:25Z"},{"alias_kind":"pith_short_16","alias_value":"K4WZPF5OEAMPPYY5","created_at":"2026-07-21T01:21:25Z"},{"alias_kind":"pith_short_8","alias_value":"K4WZPF5O","created_at":"2026-07-21T01:21:25Z"}],"graph_snapshots":[{"event_id":"sha256:06731a61da1a4dd1b4c0e5c91a58d00d3ff287f11a0dc7699e534b99c51468aa","target":"graph","created_at":"2026-07-21T01:21:25Z","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/2607.17281/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Auto-bidding plays an essential role in online advertising, automatically adjusting bids for advertisers to optimize their commercial goals. The emerging AI-Generated Bidding (AIGB) paradigm widely adopts generative modeling to optimize bidding strategies, yet suffers from the limited mode coverage of offline datasets and inadequate task-state understanding, hindering effective exploration of optimal strategies. Large Language Models (LLMs), with prior world knowledge and reasoning capabilities, offer a promising approach to overcome these limitations. However, directly applying LLMs to auto-b","authors_text":"Bo Zheng, Chuan Yu, Hesong Wang, Jian Xu, Qi Qi, Tianyu Wang, Xinyu Zhang, Yuejia Dou, Zhilin Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-19T14:59:12Z","title":"AIGB-R1: Self-Evolving Generative Auto-Bidding via Hierarchical Planner-Executor Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.17281","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:cad1919f4965c0d15dea1fa697927c30cc6dfcf064568dec1602015faff8c026","target":"record","created_at":"2026-07-21T01:21:25Z","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":"b0abe2f79720b83c0bc421c597684ec872ff7955a3462c6cbf5d48254462a149","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-19T14:59:12Z","title_canon_sha256":"3ddaadc0b451bae6b41c0e38864446df0c3b15c1113ffeec25fc0da10d4662c0"},"schema_version":"1.0","source":{"id":"2607.17281","kind":"arxiv","version":1}},"canonical_sha256":"572d9797ae2018f7e31d4a3630f1f7348976594c0fdacc7c879e7a0d132fdbd7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"572d9797ae2018f7e31d4a3630f1f7348976594c0fdacc7c879e7a0d132fdbd7","first_computed_at":"2026-07-21T01:21:25.227434Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-21T01:21:25.227434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qElJw+b/h5jqs1iZF/NW3C1j+7ge1+ccOsDA35YmHDhAXlhx3a4/4tvv8ntWKURJt5nsvMFJdwDUYc7clfaWBg==","signature_status":"signed_v1","signed_at":"2026-07-21T01:21:25.228241Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.17281","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cad1919f4965c0d15dea1fa697927c30cc6dfcf064568dec1602015faff8c026","sha256:06731a61da1a4dd1b4c0e5c91a58d00d3ff287f11a0dc7699e534b99c51468aa"],"state_sha256":"016228d8d6d9989d02a4b16b2184f59260918d57d7ca5807cdaf64f027df87b7"}