{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:IL5F52LVGALVM3IWDJTB5ZUPNY","short_pith_number":"pith:IL5F52LV","canonical_record":{"source":{"id":"2505.02360","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-05T04:41:21Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"98aa014675ea30d15da681371998020cccc8bf4e1e4e1901899a5dd8eccf551c","abstract_canon_sha256":"646c48386788079cb41ff06def1ee7e4c0f457daa6db0c6b1499489b333a7ed9"},"schema_version":"1.0"},"canonical_sha256":"42fa5ee9753017566d161a661ee68f6e14fb72318d198feffbf8523902600837","source":{"kind":"arxiv","id":"2505.02360","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.02360","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"arxiv_version","alias_value":"2505.02360v2","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.02360","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"pith_short_12","alias_value":"IL5F52LVGALV","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"pith_short_16","alias_value":"IL5F52LVGALVM3IW","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"pith_short_8","alias_value":"IL5F52LV","created_at":"2026-05-20T00:02:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:IL5F52LVGALVM3IWDJTB5ZUPNY","target":"record","payload":{"canonical_record":{"source":{"id":"2505.02360","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-05T04:41:21Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"98aa014675ea30d15da681371998020cccc8bf4e1e4e1901899a5dd8eccf551c","abstract_canon_sha256":"646c48386788079cb41ff06def1ee7e4c0f457daa6db0c6b1499489b333a7ed9"},"schema_version":"1.0"},"canonical_sha256":"42fa5ee9753017566d161a661ee68f6e14fb72318d198feffbf8523902600837","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:49.900363Z","signature_b64":"Co2t7ia1sqOceyNxiZ3zcocGCZn6X0DIFrMYRyBteyW4Z8iRA9K7BNjwqV3ZFzqe3sZ0z4vqIfQ8ZvCC42K9AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"42fa5ee9753017566d161a661ee68f6e14fb72318d198feffbf8523902600837","last_reissued_at":"2026-05-20T00:02:49.899399Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:49.899399Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.02360","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:02:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7Su/NhzBDbGdRJJOd9GBCYkwifrBZ++jOpBGbqJVkJRQH7Cz1K7U0zh2J5r7RG/aiLwyGD0gbOUdHRDdCD+pCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T07:09:38.374913Z"},"content_sha256":"756b1074b93147d6b5188c4e80412dc8f007f7afaf9e4da70a47686e8cc411ba","schema_version":"1.0","event_id":"sha256:756b1074b93147d6b5188c4e80412dc8f007f7afaf9e4da70a47686e8cc411ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:IL5F52LVGALVM3IWDJTB5ZUPNY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Catastrophic Overfitting, Entropy Gap and Participation Ratio: A Noiseless $l^p$ Norm Solution for Fast Adversarial Training","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Fares B. Mehouachi, Saif Eddin Jabari","submitted_at":"2025-05-05T04:41:21Z","abstract_excerpt":"Adversarial training is a cornerstone of robust deep learning, but fast methods like the Fast Gradient Sign Method (FGSM) often suffer from Catastrophic Overfitting (CO), where models become robust to single-step attacks but fail against multi-step variants. While existing solutions rely on noise injection, regularization, or gradient clipping, we propose a novel solution that purely controls the $l^p$ training norm to mitigate CO. Our study is motivated by the empirical observation that CO is more prevalent under the $l^{\\infty}$ norm than the $l^2$ norm. Leveraging this insight, we develop a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.02360","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.02360/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:02:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2uCwMAEPxtQ43xWuN4ENv9S92iXH6aPrJXdm8Qxq/wQB4sy48zf49FMcUer20A8SzvC/sHuM/XVA5cpYKeO3Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T07:09:38.375603Z"},"content_sha256":"1e0e87b83fe3ba468a6b6ebe15e653a6a3c48508b72c92cf46777e6041c08bea","schema_version":"1.0","event_id":"sha256:1e0e87b83fe3ba468a6b6ebe15e653a6a3c48508b72c92cf46777e6041c08bea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IL5F52LVGALVM3IWDJTB5ZUPNY/bundle.json","state_url":"https://pith.science/pith/IL5F52LVGALVM3IWDJTB5ZUPNY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IL5F52LVGALVM3IWDJTB5ZUPNY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T07:09:38Z","links":{"resolver":"https://pith.science/pith/IL5F52LVGALVM3IWDJTB5ZUPNY","bundle":"https://pith.science/pith/IL5F52LVGALVM3IWDJTB5ZUPNY/bundle.json","state":"https://pith.science/pith/IL5F52LVGALVM3IWDJTB5ZUPNY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IL5F52LVGALVM3IWDJTB5ZUPNY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:IL5F52LVGALVM3IWDJTB5ZUPNY","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":"646c48386788079cb41ff06def1ee7e4c0f457daa6db0c6b1499489b333a7ed9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-05T04:41:21Z","title_canon_sha256":"98aa014675ea30d15da681371998020cccc8bf4e1e4e1901899a5dd8eccf551c"},"schema_version":"1.0","source":{"id":"2505.02360","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.02360","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"arxiv_version","alias_value":"2505.02360v2","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.02360","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"pith_short_12","alias_value":"IL5F52LVGALV","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"pith_short_16","alias_value":"IL5F52LVGALVM3IW","created_at":"2026-05-20T00:02:49Z"},{"alias_kind":"pith_short_8","alias_value":"IL5F52LV","created_at":"2026-05-20T00:02:49Z"}],"graph_snapshots":[{"event_id":"sha256:1e0e87b83fe3ba468a6b6ebe15e653a6a3c48508b72c92cf46777e6041c08bea","target":"graph","created_at":"2026-05-20T00:02:49Z","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/2505.02360/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adversarial training is a cornerstone of robust deep learning, but fast methods like the Fast Gradient Sign Method (FGSM) often suffer from Catastrophic Overfitting (CO), where models become robust to single-step attacks but fail against multi-step variants. While existing solutions rely on noise injection, regularization, or gradient clipping, we propose a novel solution that purely controls the $l^p$ training norm to mitigate CO. Our study is motivated by the empirical observation that CO is more prevalent under the $l^{\\infty}$ norm than the $l^2$ norm. Leveraging this insight, we develop a","authors_text":"Fares B. Mehouachi, Saif Eddin Jabari","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-05T04:41:21Z","title":"Catastrophic Overfitting, Entropy Gap and Participation Ratio: A Noiseless $l^p$ Norm Solution for Fast Adversarial Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.02360","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":"sha256:756b1074b93147d6b5188c4e80412dc8f007f7afaf9e4da70a47686e8cc411ba","target":"record","created_at":"2026-05-20T00:02:49Z","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":"646c48386788079cb41ff06def1ee7e4c0f457daa6db0c6b1499489b333a7ed9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-05T04:41:21Z","title_canon_sha256":"98aa014675ea30d15da681371998020cccc8bf4e1e4e1901899a5dd8eccf551c"},"schema_version":"1.0","source":{"id":"2505.02360","kind":"arxiv","version":2}},"canonical_sha256":"42fa5ee9753017566d161a661ee68f6e14fb72318d198feffbf8523902600837","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"42fa5ee9753017566d161a661ee68f6e14fb72318d198feffbf8523902600837","first_computed_at":"2026-05-20T00:02:49.899399Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:49.899399Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Co2t7ia1sqOceyNxiZ3zcocGCZn6X0DIFrMYRyBteyW4Z8iRA9K7BNjwqV3ZFzqe3sZ0z4vqIfQ8ZvCC42K9AA==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:49.900363Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.02360","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:756b1074b93147d6b5188c4e80412dc8f007f7afaf9e4da70a47686e8cc411ba","sha256:1e0e87b83fe3ba468a6b6ebe15e653a6a3c48508b72c92cf46777e6041c08bea"],"state_sha256":"eef945d11082d6e06f257f540b4f3a2d896978b027fb04ab7106b7f14ab8b626"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eLIvx5fZ5iE/XEOK0fA+WOWdAnt4GKLvvlD7QICu2GnoskydutNmOwP2/hJKsr1rRy7LgmWqinzTg/ObrcLsDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T07:09:38.378594Z","bundle_sha256":"48415cd98b03ee87df28e75d705546b5aa193d519624a4755ed84a22ae6d61ca"}}