{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:S6VLFIKDMVPVR546MSOG72HCFF","short_pith_number":"pith:S6VLFIKD","schema_version":"1.0","canonical_sha256":"97aab2a143655f58f79e649c6fe8e22963bf70fa78831f6f3431755089578dd1","source":{"kind":"arxiv","id":"2312.02237","version":1},"attestation_state":"computed","paper":{"title":"Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guanlin Li, Jie Zhang, Man Zhou, Naishan Zheng, Tianwei Zhang","submitted_at":"2023-12-04T09:07:30Z","abstract_excerpt":"Adversarial examples are one of the most severe threats to deep learning models. Numerous works have been proposed to study and defend adversarial examples. However, these works lack analysis of adversarial information or perturbation, which cannot reveal the mystery of adversarial examples and lose proper interpretation. In this paper, we aim to fill this gap by studying adversarial information as unstructured noise, which does not have a clear pattern. Specifically, we provide some empirical studies with singular value decomposition, by decomposing images into several matrices, to analyze ad"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2312.02237","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-04T09:07:30Z","cross_cats_sorted":[],"title_canon_sha256":"d4e4191c2a54579fdbd1813e42afb5ca8b3c161864acdaa60f1c40dbcf91d906","abstract_canon_sha256":"dadfa39b4da660e6d6ef4a775b5fcd88f756054772f26331f03bda9abb917dac"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:20:14.883305Z","signature_b64":"rPewISzTBx9HwmunE1oKkTy3knZpNSwoBzRhL0VrptjtlOq3SLsbsCllJqrBYzz694qoFIZ0DpMAohMbhH7DCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97aab2a143655f58f79e649c6fe8e22963bf70fa78831f6f3431755089578dd1","last_reissued_at":"2026-07-05T07:20:14.882865Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:20:14.882865Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Singular Regularization with Information Bottleneck Improves Model's Adversarial Robustness","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guanlin Li, Jie Zhang, Man Zhou, Naishan Zheng, Tianwei Zhang","submitted_at":"2023-12-04T09:07:30Z","abstract_excerpt":"Adversarial examples are one of the most severe threats to deep learning models. Numerous works have been proposed to study and defend adversarial examples. However, these works lack analysis of adversarial information or perturbation, which cannot reveal the mystery of adversarial examples and lose proper interpretation. In this paper, we aim to fill this gap by studying adversarial information as unstructured noise, which does not have a clear pattern. Specifically, we provide some empirical studies with singular value decomposition, by decomposing images into several matrices, to analyze ad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02237","kind":"arxiv","version":1},"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/2312.02237/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2312.02237","created_at":"2026-07-05T07:20:14.882924+00:00"},{"alias_kind":"arxiv_version","alias_value":"2312.02237v1","created_at":"2026-07-05T07:20:14.882924+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02237","created_at":"2026-07-05T07:20:14.882924+00:00"},{"alias_kind":"pith_short_12","alias_value":"S6VLFIKDMVPV","created_at":"2026-07-05T07:20:14.882924+00:00"},{"alias_kind":"pith_short_16","alias_value":"S6VLFIKDMVPVR546","created_at":"2026-07-05T07:20:14.882924+00:00"},{"alias_kind":"pith_short_8","alias_value":"S6VLFIKD","created_at":"2026-07-05T07:20:14.882924+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF","json":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF.json","graph_json":"https://pith.science/api/pith-number/S6VLFIKDMVPVR546MSOG72HCFF/graph.json","events_json":"https://pith.science/api/pith-number/S6VLFIKDMVPVR546MSOG72HCFF/events.json","paper":"https://pith.science/paper/S6VLFIKD"},"agent_actions":{"view_html":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF","download_json":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF.json","view_paper":"https://pith.science/paper/S6VLFIKD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2312.02237&json=true","fetch_graph":"https://pith.science/api/pith-number/S6VLFIKDMVPVR546MSOG72HCFF/graph.json","fetch_events":"https://pith.science/api/pith-number/S6VLFIKDMVPVR546MSOG72HCFF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF/action/storage_attestation","attest_author":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF/action/author_attestation","sign_citation":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF/action/citation_signature","submit_replication":"https://pith.science/pith/S6VLFIKDMVPVR546MSOG72HCFF/action/replication_record"}},"created_at":"2026-07-05T07:20:14.882924+00:00","updated_at":"2026-07-05T07:20:14.882924+00:00"}