{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:2NAO2W2223MWYGLXUR2CCO3BAZ","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":"92c114e8b0ab9aee5974f2c7b302fb5300766dad27cecca8cb232f788be01933","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-15T08:18:33Z","title_canon_sha256":"d391f1676e666ed2d4cd2b4743a4236b053e925c56a24db65a2fdab37b46363d"},"schema_version":"1.0","source":{"id":"1801.04695","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.04695","created_at":"2026-05-18T00:12:53Z"},{"alias_kind":"arxiv_version","alias_value":"1801.04695v3","created_at":"2026-05-18T00:12:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.04695","created_at":"2026-05-18T00:12:53Z"},{"alias_kind":"pith_short_12","alias_value":"2NAO2W2223MW","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2NAO2W2223MWYGLX","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2NAO2W22","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:52cb9a7100957aeadf52db1cfebce5304ff96db78222b2c8b0a81a0bfe79791c","target":"graph","created_at":"2026-05-18T00:12:53Z","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"},"paper":{"abstract_excerpt":"Deep neural networks represent the state of the art in machine learning in a growing number of fields, including vision, speech and natural language processing. However, recent work raises important questions about the robustness of such architectures, by showing that it is possible to induce classification errors through tiny, almost imperceptible, perturbations. Vulnerability to such \"adversarial attacks\", or \"adversarial examples\", has been conjectured to be due to the excessive linearity of deep networks. In this paper, we study this phenomenon in the setting of a linear classifier, and sh","authors_text":"Ramtin Pedarsani, Soorya Gopalakrishnan, Upamanyu Madhow, Zhinus Marzi","cross_cats":["cs.IT","cs.LG","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-15T08:18:33Z","title":"Sparsity-based Defense against Adversarial Attacks on Linear Classifiers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.04695","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":"sha256:77cb82c8e0bff2bc7a4f3cfb84f442c42f7e66b40e618773e48e116a975c3d86","target":"record","created_at":"2026-05-18T00:12:53Z","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":"92c114e8b0ab9aee5974f2c7b302fb5300766dad27cecca8cb232f788be01933","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-15T08:18:33Z","title_canon_sha256":"d391f1676e666ed2d4cd2b4743a4236b053e925c56a24db65a2fdab37b46363d"},"schema_version":"1.0","source":{"id":"1801.04695","kind":"arxiv","version":3}},"canonical_sha256":"d340ed5b5ad6d96c1977a474213b6106630a5afce6bffc94ce206e8a80b5d1a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d340ed5b5ad6d96c1977a474213b6106630a5afce6bffc94ce206e8a80b5d1a8","first_computed_at":"2026-05-18T00:12:53.533714Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:12:53.533714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"23gdbXuKzPmiUNvXkG0b+teoqPk3A4wgCVyuxVBgKOWlnTxG7kHOdKhaLLabGLR4fW9jtZHbo/F3nvjtZzUTAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:12:53.534258Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.04695","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77cb82c8e0bff2bc7a4f3cfb84f442c42f7e66b40e618773e48e116a975c3d86","sha256:52cb9a7100957aeadf52db1cfebce5304ff96db78222b2c8b0a81a0bfe79791c"],"state_sha256":"d05a26daec79e86bb7577d5471e2a8224e200e0557b70b2946ac99577b8b730a"}