{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:IHYVWFAD2A4HYMWTYJICJRH4UN","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":"7ad4885d4ecb79140dabc22ed3e5f14d2eef05d921488c38762cc5eb3ca40550","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T12:36:50Z","title_canon_sha256":"ceba45f1018c348590ea2f98336323979f49613d7ab19908d793f32377dde8a5"},"schema_version":"1.0","source":{"id":"2211.05523","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.05523","created_at":"2026-07-05T07:22:14Z"},{"alias_kind":"arxiv_version","alias_value":"2211.05523v3","created_at":"2026-07-05T07:22:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.05523","created_at":"2026-07-05T07:22:14Z"},{"alias_kind":"pith_short_12","alias_value":"IHYVWFAD2A4H","created_at":"2026-07-05T07:22:14Z"},{"alias_kind":"pith_short_16","alias_value":"IHYVWFAD2A4HYMWT","created_at":"2026-07-05T07:22:14Z"},{"alias_kind":"pith_short_8","alias_value":"IHYVWFAD","created_at":"2026-07-05T07:22:14Z"}],"graph_snapshots":[{"event_id":"sha256:b590da1bd1afa125081702aa196418820fdeb81214880a45006dd511dd9e0388","target":"graph","created_at":"2026-07-05T07:22:14Z","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/2211.05523/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adversarial training is widely acknowledged as the most effective defense against adversarial attacks. However, it is also well established that achieving both robustness and generalization in adversarially trained models involves a trade-off. The goal of this work is to provide an in depth comparison of different approaches for adversarial training in language models. Specifically, we study the effect of pre-training data augmentation as well as training time input perturbations vs. embedding space perturbations on the robustness and generalization of transformer-based language models. Our fi","authors_text":"Enes Altinisik, Hassan Sajjad, Husrev Taha Sencar, Safa Messaoud, Sanjay Chawla","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T12:36:50Z","title":"Impact of Adversarial Training on Robustness and Generalizability of Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.05523","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":"sha256:6bfdf47388be8f4df89707747c85097989fca306c72e5a548565cdfd462bf2bc","target":"record","created_at":"2026-07-05T07:22:14Z","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":"7ad4885d4ecb79140dabc22ed3e5f14d2eef05d921488c38762cc5eb3ca40550","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T12:36:50Z","title_canon_sha256":"ceba45f1018c348590ea2f98336323979f49613d7ab19908d793f32377dde8a5"},"schema_version":"1.0","source":{"id":"2211.05523","kind":"arxiv","version":3}},"canonical_sha256":"41f15b1403d0387c32d3c25024c4fca37b8770e853cfd80bab342f266499551b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"41f15b1403d0387c32d3c25024c4fca37b8770e853cfd80bab342f266499551b","first_computed_at":"2026-07-05T07:22:14.041804Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:22:14.041804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mFhYXElrHn7U3vSfPUY37Eo2rG8HuBbVxhSvDpJiZhMSovhcQhJjmPYeU+gseFrTbqvX+6w5AL9hfPMS0hVuBg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:22:14.042244Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.05523","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6bfdf47388be8f4df89707747c85097989fca306c72e5a548565cdfd462bf2bc","sha256:b590da1bd1afa125081702aa196418820fdeb81214880a45006dd511dd9e0388"],"state_sha256":"2a776d9b4da6a8cc809037484f8721b32955d5eec7ffc234718ff9d6314845bb"}