{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:U3C3Q372TNO7UZE4H54U7ZDSM5","short_pith_number":"pith:U3C3Q372","canonical_record":{"source":{"id":"1904.02405","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-04T08:31:15Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"fe6358128769841d563ae77076420d737d38d58179fc4483756760709443b8f2","abstract_canon_sha256":"d54ac026bcc7726f5af63e5a00f2fe0a4c54da301522de18e5d48970d6ef913a"},"schema_version":"1.0"},"canonical_sha256":"a6c5b86ffa9b5dfa649c3f794fe472675dbb37c697c9a88a842588b964b7f492","source":{"kind":"arxiv","id":"1904.02405","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.02405","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"arxiv_version","alias_value":"1904.02405v1","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02405","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"pith_short_12","alias_value":"U3C3Q372TNO7","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"U3C3Q372TNO7UZE4","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"U3C3Q372","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:U3C3Q372TNO7UZE4H54U7ZDSM5","target":"record","payload":{"canonical_record":{"source":{"id":"1904.02405","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-04T08:31:15Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"fe6358128769841d563ae77076420d737d38d58179fc4483756760709443b8f2","abstract_canon_sha256":"d54ac026bcc7726f5af63e5a00f2fe0a4c54da301522de18e5d48970d6ef913a"},"schema_version":"1.0"},"canonical_sha256":"a6c5b86ffa9b5dfa649c3f794fe472675dbb37c697c9a88a842588b964b7f492","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:23.783273Z","signature_b64":"Bn9pBfzPGJ47WPjosytaAjIhKt+KUK1rsRFlKle6LwpNPEsxiBR3w6YFVgZIxyxO7Z/lDpL7MDaIDlZoLMz8CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a6c5b86ffa9b5dfa649c3f794fe472675dbb37c697c9a88a842588b964b7f492","last_reissued_at":"2026-05-17T23:49:23.782858Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:23.782858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.02405","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":"2026-05-17T23:49:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LL9HJNMQ9tt5Ko8GUcCFCwqLMs5H3cbrNjASEJmF0CqilcxEMMBQ2O99Q44I/IiokiUXNjcXiYfiulMB8CseAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:49:27.054844Z"},"content_sha256":"19df8de13160677d9d987aa9f91f22a27dbc2850839ea5e8fa4e2aa366af7f97","schema_version":"1.0","event_id":"sha256:19df8de13160677d9d987aa9f91f22a27dbc2850839ea5e8fa4e2aa366af7f97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:U3C3Q372TNO7UZE4H54U7ZDSM5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Jonathan Berant, Or Gorodissky, Yoav Chai, Yotam Gil","submitted_at":"2019-04-04T08:31:15Z","abstract_excerpt":"Adversarial examples are important for understanding the behavior of neural models, and can improve their robustness through adversarial training. Recent work in natural language processing generated adversarial examples by assuming white-box access to the attacked model, and optimizing the input directly against it (Ebrahimi et al., 2018). In this work, we show that the knowledge implicit in the optimization procedure can be distilled into another more efficient neural network. We train a model to emulate the behavior of a white-box attack and show that it generalizes well across examples. Mo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02405","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":""},"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":"2026-05-17T23:49:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BDX4lKrsWVGx5h5zhmEb3Uq+ci+MciYPb3KG+Ivq+ek6TKHov19kyCR7iXD1i1rmENdLtwN73jAxzV6vjQ5fBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:49:27.055193Z"},"content_sha256":"773ce0fb8c48da912f010c3e0af9b4992cbb343b7e4a6d3b76a54d61d15739b4","schema_version":"1.0","event_id":"sha256:773ce0fb8c48da912f010c3e0af9b4992cbb343b7e4a6d3b76a54d61d15739b4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U3C3Q372TNO7UZE4H54U7ZDSM5/bundle.json","state_url":"https://pith.science/pith/U3C3Q372TNO7UZE4H54U7ZDSM5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U3C3Q372TNO7UZE4H54U7ZDSM5/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":"2026-05-30T13:49:27Z","links":{"resolver":"https://pith.science/pith/U3C3Q372TNO7UZE4H54U7ZDSM5","bundle":"https://pith.science/pith/U3C3Q372TNO7UZE4H54U7ZDSM5/bundle.json","state":"https://pith.science/pith/U3C3Q372TNO7UZE4H54U7ZDSM5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U3C3Q372TNO7UZE4H54U7ZDSM5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:U3C3Q372TNO7UZE4H54U7ZDSM5","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":"d54ac026bcc7726f5af63e5a00f2fe0a4c54da301522de18e5d48970d6ef913a","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-04T08:31:15Z","title_canon_sha256":"fe6358128769841d563ae77076420d737d38d58179fc4483756760709443b8f2"},"schema_version":"1.0","source":{"id":"1904.02405","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.02405","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"arxiv_version","alias_value":"1904.02405v1","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02405","created_at":"2026-05-17T23:49:23Z"},{"alias_kind":"pith_short_12","alias_value":"U3C3Q372TNO7","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"U3C3Q372TNO7UZE4","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"U3C3Q372","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:773ce0fb8c48da912f010c3e0af9b4992cbb343b7e4a6d3b76a54d61d15739b4","target":"graph","created_at":"2026-05-17T23:49:23Z","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 examples are important for understanding the behavior of neural models, and can improve their robustness through adversarial training. Recent work in natural language processing generated adversarial examples by assuming white-box access to the attacked model, and optimizing the input directly against it (Ebrahimi et al., 2018). In this work, we show that the knowledge implicit in the optimization procedure can be distilled into another more efficient neural network. We train a model to emulate the behavior of a white-box attack and show that it generalizes well across examples. Mo","authors_text":"Jonathan Berant, Or Gorodissky, Yoav Chai, Yotam Gil","cross_cats":["cs.CR","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-04T08:31:15Z","title":"White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02405","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":"sha256:19df8de13160677d9d987aa9f91f22a27dbc2850839ea5e8fa4e2aa366af7f97","target":"record","created_at":"2026-05-17T23:49:23Z","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":"d54ac026bcc7726f5af63e5a00f2fe0a4c54da301522de18e5d48970d6ef913a","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-04T08:31:15Z","title_canon_sha256":"fe6358128769841d563ae77076420d737d38d58179fc4483756760709443b8f2"},"schema_version":"1.0","source":{"id":"1904.02405","kind":"arxiv","version":1}},"canonical_sha256":"a6c5b86ffa9b5dfa649c3f794fe472675dbb37c697c9a88a842588b964b7f492","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a6c5b86ffa9b5dfa649c3f794fe472675dbb37c697c9a88a842588b964b7f492","first_computed_at":"2026-05-17T23:49:23.782858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:23.782858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bn9pBfzPGJ47WPjosytaAjIhKt+KUK1rsRFlKle6LwpNPEsxiBR3w6YFVgZIxyxO7Z/lDpL7MDaIDlZoLMz8CQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:23.783273Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.02405","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:19df8de13160677d9d987aa9f91f22a27dbc2850839ea5e8fa4e2aa366af7f97","sha256:773ce0fb8c48da912f010c3e0af9b4992cbb343b7e4a6d3b76a54d61d15739b4"],"state_sha256":"a45e551d73af3a9656eceb34ece528959107e58b4ab233f39c5639f7b167abd4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qHo2zhBYU1xh+gkdlL+bnvWvgbxfJBkguBNzshh+L4ldbGgyBOwF2YrI7WlUvN2WVzGIGrN3mNFZ76bzaJxyAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T13:49:27.057421Z","bundle_sha256":"3d9f918aff58b0c5efe0c9b46783f827f62da8250c42a0ef5d89a1ea4a308aec"}}