{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:FM3E5DPBYBURFCOO7QA4723JPX","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":"45b0eba7b6f52c7f97c3e032499ae810b1881d7142d3a084f296e5c78817bcc4","cross_cats_sorted":["math.OC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-13T19:36:50Z","title_canon_sha256":"c9858c1cca7bbd05da90cfc780725b8ba71c0a72ed74c4815392f0f1df1e4f1e"},"schema_version":"1.0","source":{"id":"2110.07004","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.07004","created_at":"2026-07-05T04:29:10Z"},{"alias_kind":"arxiv_version","alias_value":"2110.07004v3","created_at":"2026-07-05T04:29:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.07004","created_at":"2026-07-05T04:29:10Z"},{"alias_kind":"pith_short_12","alias_value":"FM3E5DPBYBUR","created_at":"2026-07-05T04:29:10Z"},{"alias_kind":"pith_short_16","alias_value":"FM3E5DPBYBURFCOO","created_at":"2026-07-05T04:29:10Z"},{"alias_kind":"pith_short_8","alias_value":"FM3E5DPB","created_at":"2026-07-05T04:29:10Z"}],"graph_snapshots":[{"event_id":"sha256:9e80e3d1c728ea97eba78df01c1951a75940e52cb433e883e8003c6a8985ce77","target":"graph","created_at":"2026-07-05T04:29:10Z","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/2110.07004/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bilevel optimization has arisen as a powerful tool in modern machine learning. However, due to the nested structure of bilevel optimization, even gradient-based methods require second-order derivative approximations via Jacobian- or/and Hessian-vector computations, which can be costly and unscalable in practice. Recently, Hessian-free bilevel schemes have been proposed to resolve this issue, where the general idea is to use zeroth- or first-order methods to approximate the full hypergradient of the bilevel problem. However, we empirically observe that such approximation can lead to large varia","authors_text":"Daouda Sow, Kaiyi Ji, Yingbin Liang","cross_cats":["math.OC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-13T19:36:50Z","title":"On the Convergence Theory for Hessian-Free Bilevel Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.07004","kind":"arxiv","version":3},"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":"sha256:5610afbb37fa96e0cbc2b8cf869c5b164ade65b023cdbf8c260da261209873b6","target":"record","created_at":"2026-07-05T04:29:10Z","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":"45b0eba7b6f52c7f97c3e032499ae810b1881d7142d3a084f296e5c78817bcc4","cross_cats_sorted":["math.OC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-13T19:36:50Z","title_canon_sha256":"c9858c1cca7bbd05da90cfc780725b8ba71c0a72ed74c4815392f0f1df1e4f1e"},"schema_version":"1.0","source":{"id":"2110.07004","kind":"arxiv","version":3}},"canonical_sha256":"2b364e8de1c0691289cefc01cfeb697df47154f2edda246aa00464a17fdda3e4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2b364e8de1c0691289cefc01cfeb697df47154f2edda246aa00464a17fdda3e4","first_computed_at":"2026-07-05T04:29:10.047250Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:29:10.047250Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KdNDL/qQOzTxCJhN94FJISPa2YN0Zagp3GPIcDN9PgWGLgNPpEC2r7AoS/IbqXpyyjwYGwfJa14NCIyvN8JLBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:29:10.047713Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.07004","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5610afbb37fa96e0cbc2b8cf869c5b164ade65b023cdbf8c260da261209873b6","sha256:9e80e3d1c728ea97eba78df01c1951a75940e52cb433e883e8003c6a8985ce77"],"state_sha256":"d066bf58fb55603ec8761a44cac82bb68cf20ae7a86ce0a5fc25acd86759aea9"}