{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:BLXILPJ3LZONL6D33ZJXXWKKIP","short_pith_number":"pith:BLXILPJ3","canonical_record":{"source":{"id":"2203.08739","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-16T16:37:17Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0fc1833b96b304e63c507c788a4b75f852099b2e4dabf17ef5eac984f6c35d95","abstract_canon_sha256":"bf08a2f075c8adabd230f0da4258a708226ec6b737bc1450a5f5ad02e248c37c"},"schema_version":"1.0"},"canonical_sha256":"0aee85bd3b5e5cd5f87bde537bd94a43c43cacb03936c1c6eb796644540199d8","source":{"kind":"arxiv","id":"2203.08739","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.08739","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"arxiv_version","alias_value":"2203.08739v1","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.08739","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"pith_short_12","alias_value":"BLXILPJ3LZON","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"pith_short_16","alias_value":"BLXILPJ3LZONL6D3","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"pith_short_8","alias_value":"BLXILPJ3","created_at":"2026-07-05T04:05:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:BLXILPJ3LZONL6D33ZJXXWKKIP","target":"record","payload":{"canonical_record":{"source":{"id":"2203.08739","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-16T16:37:17Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0fc1833b96b304e63c507c788a4b75f852099b2e4dabf17ef5eac984f6c35d95","abstract_canon_sha256":"bf08a2f075c8adabd230f0da4258a708226ec6b737bc1450a5f5ad02e248c37c"},"schema_version":"1.0"},"canonical_sha256":"0aee85bd3b5e5cd5f87bde537bd94a43c43cacb03936c1c6eb796644540199d8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:05:47.939051Z","signature_b64":"Nf3Jrw5pBro5Fi/R0864KSTx32gLRF4JLaI5fgLWl+FsFVMM0Q754zG0NIx/Qp/tr/0n05P4E/FdPmgvYOGKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0aee85bd3b5e5cd5f87bde537bd94a43c43cacb03936c1c6eb796644540199d8","last_reissued_at":"2026-07-05T04:05:47.938518Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:05:47.938518Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.08739","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:05:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H2UWhGZkjvZBKEq9Ioqke4Ivs/gqNZ3+kJ0XzU0NTODnzGp8/ZnTA1V0Lemm2ztL+TLzR9Wu9aubLo2JjH1fAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T18:41:04.578497Z"},"content_sha256":"abc2feddc000c88d296b669764b648203c5b4804e5bd2ead0c27b603115ed191","schema_version":"1.0","event_id":"sha256:abc2feddc000c88d296b669764b648203c5b4804e5bd2ead0c27b603115ed191"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:BLXILPJ3LZONL6D33ZJXXWKKIP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"What Do Adversarially trained Neural Networks Focus: A Fourier Domain-based Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Binxiao Huang, Chaofan Tao, Ngai Wong, Rui Lin","submitted_at":"2022-03-16T16:37:17Z","abstract_excerpt":"Although many fields have witnessed the superior performance brought about by deep learning, the robustness of neural networks remains an open issue. Specifically, a small adversarial perturbation on the input may cause the model to produce a completely different output. Such poor robustness implies many potential hazards, especially in security-critical applications, e.g., autonomous driving and mobile robotics. This work studies what information the adversarially trained model focuses on. Empirically, we notice that the differences between the clean and adversarial data are mainly distribute"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.08739","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/2203.08739/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":"2026-07-05T04:05:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Iu32IfDW0JUB8zxdvsDz46+2ErNy9DLbhk3NPUV3rG3e5jSQjJd2Gmilt9YL+rsust3bXwhm/tTe8b/L6JT7AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T18:41:04.578816Z"},"content_sha256":"879209c1849174a1a9296e3b6fc52be03ad4ceaf3530d8787360f4f213db7802","schema_version":"1.0","event_id":"sha256:879209c1849174a1a9296e3b6fc52be03ad4ceaf3530d8787360f4f213db7802"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BLXILPJ3LZONL6D33ZJXXWKKIP/bundle.json","state_url":"https://pith.science/pith/BLXILPJ3LZONL6D33ZJXXWKKIP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BLXILPJ3LZONL6D33ZJXXWKKIP/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":"2026-07-31T18:41:04Z","links":{"resolver":"https://pith.science/pith/BLXILPJ3LZONL6D33ZJXXWKKIP","bundle":"https://pith.science/pith/BLXILPJ3LZONL6D33ZJXXWKKIP/bundle.json","state":"https://pith.science/pith/BLXILPJ3LZONL6D33ZJXXWKKIP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BLXILPJ3LZONL6D33ZJXXWKKIP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:BLXILPJ3LZONL6D33ZJXXWKKIP","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":"bf08a2f075c8adabd230f0da4258a708226ec6b737bc1450a5f5ad02e248c37c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-16T16:37:17Z","title_canon_sha256":"0fc1833b96b304e63c507c788a4b75f852099b2e4dabf17ef5eac984f6c35d95"},"schema_version":"1.0","source":{"id":"2203.08739","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.08739","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"arxiv_version","alias_value":"2203.08739v1","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.08739","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"pith_short_12","alias_value":"BLXILPJ3LZON","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"pith_short_16","alias_value":"BLXILPJ3LZONL6D3","created_at":"2026-07-05T04:05:47Z"},{"alias_kind":"pith_short_8","alias_value":"BLXILPJ3","created_at":"2026-07-05T04:05:47Z"}],"graph_snapshots":[{"event_id":"sha256:879209c1849174a1a9296e3b6fc52be03ad4ceaf3530d8787360f4f213db7802","target":"graph","created_at":"2026-07-05T04:05:47Z","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/2203.08739/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although many fields have witnessed the superior performance brought about by deep learning, the robustness of neural networks remains an open issue. Specifically, a small adversarial perturbation on the input may cause the model to produce a completely different output. Such poor robustness implies many potential hazards, especially in security-critical applications, e.g., autonomous driving and mobile robotics. This work studies what information the adversarially trained model focuses on. Empirically, we notice that the differences between the clean and adversarial data are mainly distribute","authors_text":"Binxiao Huang, Chaofan Tao, Ngai Wong, Rui Lin","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-16T16:37:17Z","title":"What Do Adversarially trained Neural Networks Focus: A Fourier Domain-based Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.08739","kind":"arxiv","version":1},"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:abc2feddc000c88d296b669764b648203c5b4804e5bd2ead0c27b603115ed191","target":"record","created_at":"2026-07-05T04:05:47Z","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":"bf08a2f075c8adabd230f0da4258a708226ec6b737bc1450a5f5ad02e248c37c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-16T16:37:17Z","title_canon_sha256":"0fc1833b96b304e63c507c788a4b75f852099b2e4dabf17ef5eac984f6c35d95"},"schema_version":"1.0","source":{"id":"2203.08739","kind":"arxiv","version":1}},"canonical_sha256":"0aee85bd3b5e5cd5f87bde537bd94a43c43cacb03936c1c6eb796644540199d8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0aee85bd3b5e5cd5f87bde537bd94a43c43cacb03936c1c6eb796644540199d8","first_computed_at":"2026-07-05T04:05:47.938518Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:05:47.938518Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nf3Jrw5pBro5Fi/R0864KSTx32gLRF4JLaI5fgLWl+FsFVMM0Q754zG0NIx/Qp/tr/0n05P4E/FdPmgvYOGKAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:05:47.939051Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.08739","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:abc2feddc000c88d296b669764b648203c5b4804e5bd2ead0c27b603115ed191","sha256:879209c1849174a1a9296e3b6fc52be03ad4ceaf3530d8787360f4f213db7802"],"state_sha256":"cba2caa26771cd1128743f096964ee8fb96867f85475b392029f2eee4273aab3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0vV90btMRQgr3IWcevPpqxrAxYF5NtzXRw5RjMRd/pi7IMW4/Maj9epV65lAX0tRhxkgzwmNpGIR9wLJJYOPDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T18:41:04.581219Z","bundle_sha256":"214473a8cd647116962af4f04fa6d5f01829dc3ef49186cdd40dc1071baf12ae"}}