{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VWUMGNQ5GKFDN3IFWT5BFM5CMV","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":"1b867e5c899950286e67e34ecef2388f831e01c52765ae15f75072fb7c952871","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-07T15:41:45Z","title_canon_sha256":"34b9da94183514ae4171c9d79b88ee9e83b2bb15634bf1c68b5b4960a09a84f2"},"schema_version":"1.0","source":{"id":"2309.03791","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.03791","created_at":"2026-07-05T11:42:19Z"},{"alias_kind":"arxiv_version","alias_value":"2309.03791v3","created_at":"2026-07-05T11:42:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.03791","created_at":"2026-07-05T11:42:19Z"},{"alias_kind":"pith_short_12","alias_value":"VWUMGNQ5GKFD","created_at":"2026-07-05T11:42:19Z"},{"alias_kind":"pith_short_16","alias_value":"VWUMGNQ5GKFDN3IF","created_at":"2026-07-05T11:42:19Z"},{"alias_kind":"pith_short_8","alias_value":"VWUMGNQ5","created_at":"2026-07-05T11:42:19Z"}],"graph_snapshots":[{"event_id":"sha256:e9c4632167dc975a315dc6e19e409d3d5d33ade389bd3574fd4ec192993e897f","target":"graph","created_at":"2026-07-05T11:42:19Z","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/2309.03791/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a new class of optimal-transport-regularized divergences, $D^c$, constructed via an infimal convolution between an information divergence, $D$, and an optimal-transport (OT) cost, $C$, and study their use in distributionally robust optimization (DRO). In particular, we propose the $ARMOR_D$ methods as novel approaches to enhancing the adversarial robustness of deep learning models. These DRO-based methods are defined by minimizing the maximum expected loss over a $D^c$-neighborhood of the empirical distribution of the training data. Viewed as a tool for constructing adversarial sa","authors_text":"Jeremiah Birrell, Reza Ebrahimi","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-07T15:41:45Z","title":"Optimal Transport Regularized Divergences: Application to Adversarial Robustness"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.03791","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":"sha256:245993df9ef5a7778afd45c9bd5b51b1eb934b731ea59611d357423f7fdf1cd2","target":"record","created_at":"2026-07-05T11:42:19Z","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":"1b867e5c899950286e67e34ecef2388f831e01c52765ae15f75072fb7c952871","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-07T15:41:45Z","title_canon_sha256":"34b9da94183514ae4171c9d79b88ee9e83b2bb15634bf1c68b5b4960a09a84f2"},"schema_version":"1.0","source":{"id":"2309.03791","kind":"arxiv","version":3}},"canonical_sha256":"ada8c3361d328a36ed05b4fa12b3a2656832ca0d4d2db17f672d004f1209f366","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ada8c3361d328a36ed05b4fa12b3a2656832ca0d4d2db17f672d004f1209f366","first_computed_at":"2026-07-05T11:42:19.812231Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:42:19.812231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VHbUiL3kLq7Z4meyeyjkl7Das2Qibl1SbyN+0hk9DFmYfNveN+M4STwwtpQYn8SeCOe6f0t8TY09ZNe5alU2Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:42:19.812644Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.03791","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:245993df9ef5a7778afd45c9bd5b51b1eb934b731ea59611d357423f7fdf1cd2","sha256:e9c4632167dc975a315dc6e19e409d3d5d33ade389bd3574fd4ec192993e897f"],"state_sha256":"fa8918d84b95e291a0dde42daaae388f69a321eb3c1743e8a887ce803119b1b0"}