{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WWMIHTBKZQNWHPUHNXYDZHMKK7","short_pith_number":"pith:WWMIHTBK","canonical_record":{"source":{"id":"1812.03411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-09T01:55:31Z","cross_cats_sorted":[],"title_canon_sha256":"4bccb9fe30eb2d6b63e4356dc62cf5e0742886ffbc23d656750c6def5fcb1e44","abstract_canon_sha256":"a7febab243d6160cd54ba71ff387fd5f29e17a0b8a42d516239b7217b21c3011"},"schema_version":"1.0"},"canonical_sha256":"b59883cc2acc1b63be876df03c9d8a57f2648c30415b49b0ad438e627a1db679","source":{"kind":"arxiv","id":"1812.03411","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.03411","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"arxiv_version","alias_value":"1812.03411v2","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03411","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"pith_short_12","alias_value":"WWMIHTBKZQNW","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WWMIHTBKZQNWHPUH","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WWMIHTBK","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WWMIHTBKZQNWHPUHNXYDZHMKK7","target":"record","payload":{"canonical_record":{"source":{"id":"1812.03411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-09T01:55:31Z","cross_cats_sorted":[],"title_canon_sha256":"4bccb9fe30eb2d6b63e4356dc62cf5e0742886ffbc23d656750c6def5fcb1e44","abstract_canon_sha256":"a7febab243d6160cd54ba71ff387fd5f29e17a0b8a42d516239b7217b21c3011"},"schema_version":"1.0"},"canonical_sha256":"b59883cc2acc1b63be876df03c9d8a57f2648c30415b49b0ad438e627a1db679","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:50:33.496650Z","signature_b64":"Co3Ed383mqWnoheeeQJ6l14eXad+BRFvviV8WhEtZXZ35Cnu8QUi/j7mZZm8kYYWCJgrH5jb/HraIHO3ZgS6Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b59883cc2acc1b63be876df03c9d8a57f2648c30415b49b0ad438e627a1db679","last_reissued_at":"2026-05-17T23:50:33.495914Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:50:33.495914Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.03411","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":"2026-05-17T23:50:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E5YISqS5goN9jlVp/J1BD2DaxCs8yBXIWCFzbjSDdE2SPptQGl5OccVcqWi6ls277XRn1QLJ+FcICbVOvVnLAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:43:21.654305Z"},"content_sha256":"0878a3f3035971044a90f7f09ba239f53e2bab332a931845ea5c5c89f1115901","schema_version":"1.0","event_id":"sha256:0878a3f3035971044a90f7f09ba239f53e2bab332a931845ea5c5c89f1115901"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WWMIHTBKZQNWHPUHNXYDZHMKK7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Feature Denoising for Improving Adversarial Robustness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alan Yuille, Cihang Xie, Kaiming He, Laurens van der Maaten, Yuxin Wu","submitted_at":"2018-12-09T01:55:31Z","abstract_excerpt":"Adversarial attacks to image classification systems present challenges to convolutional networks and opportunities for understanding them. This study suggests that adversarial perturbations on images lead to noise in the features constructed by these networks. Motivated by this observation, we develop new network architectures that increase adversarial robustness by performing feature denoising. Specifically, our networks contain blocks that denoise the features using non-local means or other filters; the entire networks are trained end-to-end. When combined with adversarial training, our feat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03411","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":""},"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":"2026-05-17T23:50:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qDUeZuQXJW2oyeVKa0k0DPKMkk5voqHBBmYzqaUr4AZdFy29VcNPteOtNfnfa3z8Z8o/uXpxkwywWD+OX1O+DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:43:21.655039Z"},"content_sha256":"f1652f6bd203bc7def69df54609dc07ad8043d3f23305782f2383fae99660908","schema_version":"1.0","event_id":"sha256:f1652f6bd203bc7def69df54609dc07ad8043d3f23305782f2383fae99660908"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7/bundle.json","state_url":"https://pith.science/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7/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":"2026-05-25T18:43:21Z","links":{"resolver":"https://pith.science/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7","bundle":"https://pith.science/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7/bundle.json","state":"https://pith.science/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WWMIHTBKZQNWHPUHNXYDZHMKK7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WWMIHTBKZQNWHPUHNXYDZHMKK7","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":"a7febab243d6160cd54ba71ff387fd5f29e17a0b8a42d516239b7217b21c3011","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-09T01:55:31Z","title_canon_sha256":"4bccb9fe30eb2d6b63e4356dc62cf5e0742886ffbc23d656750c6def5fcb1e44"},"schema_version":"1.0","source":{"id":"1812.03411","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.03411","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"arxiv_version","alias_value":"1812.03411v2","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03411","created_at":"2026-05-17T23:50:33Z"},{"alias_kind":"pith_short_12","alias_value":"WWMIHTBKZQNW","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WWMIHTBKZQNWHPUH","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WWMIHTBK","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:f1652f6bd203bc7def69df54609dc07ad8043d3f23305782f2383fae99660908","target":"graph","created_at":"2026-05-17T23:50:33Z","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":"Adversarial attacks to image classification systems present challenges to convolutional networks and opportunities for understanding them. This study suggests that adversarial perturbations on images lead to noise in the features constructed by these networks. Motivated by this observation, we develop new network architectures that increase adversarial robustness by performing feature denoising. Specifically, our networks contain blocks that denoise the features using non-local means or other filters; the entire networks are trained end-to-end. When combined with adversarial training, our feat","authors_text":"Alan Yuille, Cihang Xie, Kaiming He, Laurens van der Maaten, Yuxin Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-09T01:55:31Z","title":"Feature Denoising for Improving Adversarial Robustness"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03411","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":"sha256:0878a3f3035971044a90f7f09ba239f53e2bab332a931845ea5c5c89f1115901","target":"record","created_at":"2026-05-17T23:50:33Z","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":"a7febab243d6160cd54ba71ff387fd5f29e17a0b8a42d516239b7217b21c3011","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-09T01:55:31Z","title_canon_sha256":"4bccb9fe30eb2d6b63e4356dc62cf5e0742886ffbc23d656750c6def5fcb1e44"},"schema_version":"1.0","source":{"id":"1812.03411","kind":"arxiv","version":2}},"canonical_sha256":"b59883cc2acc1b63be876df03c9d8a57f2648c30415b49b0ad438e627a1db679","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b59883cc2acc1b63be876df03c9d8a57f2648c30415b49b0ad438e627a1db679","first_computed_at":"2026-05-17T23:50:33.495914Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:50:33.495914Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Co3Ed383mqWnoheeeQJ6l14eXad+BRFvviV8WhEtZXZ35Cnu8QUi/j7mZZm8kYYWCJgrH5jb/HraIHO3ZgS6Bg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:50:33.496650Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.03411","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0878a3f3035971044a90f7f09ba239f53e2bab332a931845ea5c5c89f1115901","sha256:f1652f6bd203bc7def69df54609dc07ad8043d3f23305782f2383fae99660908"],"state_sha256":"8e36f8f3212eb4bd0fb6c07ae781717281d8f2022bfaa458fa8e56a45948c4ae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9i0FAcG+AMq7KFxxFR9L7Ys00RFUaODCF3eTkaToq6NanAUmWSyRZLwLEddDKNbxHk6DyQ6L/xrBTNAON7RZCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T18:43:21.658785Z","bundle_sha256":"6b7bbb8c9a444c0cbbdc3ae1aa14145a0e62cd9ff0bce4b46429cabc13e0697b"}}