{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:YCFMLFP4OTEUIPQ46CUTDELZOQ","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":"0ee474879bb86ff9e512846959ef04f0c324198fe63b0afc8d16550f0332fa0e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-12-23T06:25:36Z","title_canon_sha256":"7c6d92790b75f1ad0802d13ab40726ac72e4396180142c339cb434f187b3ea4a"},"schema_version":"1.0","source":{"id":"2112.12376","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.12376","created_at":"2026-07-05T05:03:34Z"},{"alias_kind":"arxiv_version","alias_value":"2112.12376v6","created_at":"2026-07-05T05:03:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.12376","created_at":"2026-07-05T05:03:34Z"},{"alias_kind":"pith_short_12","alias_value":"YCFMLFP4OTEU","created_at":"2026-07-05T05:03:34Z"},{"alias_kind":"pith_short_16","alias_value":"YCFMLFP4OTEUIPQ4","created_at":"2026-07-05T05:03:34Z"},{"alias_kind":"pith_short_8","alias_value":"YCFMLFP4","created_at":"2026-07-05T05:03:34Z"}],"graph_snapshots":[{"event_id":"sha256:e213ff223394faa63863f970297209798747dec829cc15bf102af7f8c927390a","target":"graph","created_at":"2026-07-05T05:03:34Z","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/2112.12376/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adversarial training (AT) is a widely recognized defense mechanism to gain the robustness of deep neural networks against adversarial attacks. It is built on min-max optimization (MMO), where the minimizer (i.e., defender) seeks a robust model to minimize the worst-case training loss in the presence of adversarial examples crafted by the maximizer (i.e., attacker). However, the conventional MMO method makes AT hard to scale. Thus, Fast-AT (Wong et al., 2020) and other recent algorithms attempt to simplify MMO by replacing its maximization step with the single gradient sign-based attack generat","authors_text":"Guanhua Zhang, Mingyi Hong, Prashant Khanduri, Shiyu Chang, Sijia Liu, Yihua Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-12-23T06:25:36Z","title":"Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.12376","kind":"arxiv","version":6},"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:a0fa1e9f3066d07d7f1c3613bdc6e4951776c68c8471886b8a248d33c446e9c9","target":"record","created_at":"2026-07-05T05:03:34Z","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":"0ee474879bb86ff9e512846959ef04f0c324198fe63b0afc8d16550f0332fa0e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-12-23T06:25:36Z","title_canon_sha256":"7c6d92790b75f1ad0802d13ab40726ac72e4396180142c339cb434f187b3ea4a"},"schema_version":"1.0","source":{"id":"2112.12376","kind":"arxiv","version":6}},"canonical_sha256":"c08ac595fc74c9443e1cf0a931917974081d921b6917fa9384a95afc750224bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c08ac595fc74c9443e1cf0a931917974081d921b6917fa9384a95afc750224bd","first_computed_at":"2026-07-05T05:03:34.408150Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:03:34.408150Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"O1wMNfNdd85M7g38EkTL9Z7hh5jjqNjpegkh+CpLkCvrV8D83t8PZL5hsPboWI7kAeAp/x4dj7fGsW7vmJStCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:03:34.408583Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.12376","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0fa1e9f3066d07d7f1c3613bdc6e4951776c68c8471886b8a248d33c446e9c9","sha256:e213ff223394faa63863f970297209798747dec829cc15bf102af7f8c927390a"],"state_sha256":"250fa1878be1693adca7df4f4717d98448e202cff3736ba330e13a3a5ffbeb3f"}