{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:MLQF2QYTRARFQBYI5TJYY27HV5","short_pith_number":"pith:MLQF2QYT","schema_version":"1.0","canonical_sha256":"62e05d43138822580708ecd38c6be7af776b44a282fdb3a64bea681ccb3d2d44","source":{"kind":"arxiv","id":"2004.05887","version":2},"attestation_state":"computed","paper":{"title":"Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bennett Kleinberg, Lewis D. Griffin, Maximilian Mozes, Pontus Stenetorp","submitted_at":"2020-04-13T12:11:36Z","abstract_excerpt":"Recent efforts have shown that neural text processing models are vulnerable to adversarial examples, but the nature of these examples is poorly understood. In this work, we show that adversarial attacks against CNN, LSTM and Transformer-based classification models perform word substitutions that are identifiable through frequency differences between replaced words and their corresponding substitutions. Based on these findings, we propose frequency-guided word substitutions (FGWS), a simple algorithm exploiting the frequency properties of adversarial word substitutions for the detection of adve"},"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":"2004.05887","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2020-04-13T12:11:36Z","cross_cats_sorted":[],"title_canon_sha256":"9350d2ad749e1c996ca4612fd4210d75e0169ddf3c20c14620adc1a30f29e25d","abstract_canon_sha256":"a151759c869cd0bd825a84f1590551b12e8f4023ee819d3d2d42f7c5dcd1a1a8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:09:38.288855Z","signature_b64":"w0KUhkRrVZZZAW1G0omz+VqvZbwQo6kzShC/L25micXlGmn1WXSweHMbEnB2mh+KI/rM/nFZ85RnUl295cF9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"62e05d43138822580708ecd38c6be7af776b44a282fdb3a64bea681ccb3d2d44","last_reissued_at":"2026-07-05T02:09:38.288428Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:09:38.288428Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bennett Kleinberg, Lewis D. Griffin, Maximilian Mozes, Pontus Stenetorp","submitted_at":"2020-04-13T12:11:36Z","abstract_excerpt":"Recent efforts have shown that neural text processing models are vulnerable to adversarial examples, but the nature of these examples is poorly understood. In this work, we show that adversarial attacks against CNN, LSTM and Transformer-based classification models perform word substitutions that are identifiable through frequency differences between replaced words and their corresponding substitutions. Based on these findings, we propose frequency-guided word substitutions (FGWS), a simple algorithm exploiting the frequency properties of adversarial word substitutions for the detection of adve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.05887","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2004.05887/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":"2004.05887","created_at":"2026-07-05T02:09:38.288482+00:00"},{"alias_kind":"arxiv_version","alias_value":"2004.05887v2","created_at":"2026-07-05T02:09:38.288482+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.05887","created_at":"2026-07-05T02:09:38.288482+00:00"},{"alias_kind":"pith_short_12","alias_value":"MLQF2QYTRARF","created_at":"2026-07-05T02:09:38.288482+00:00"},{"alias_kind":"pith_short_16","alias_value":"MLQF2QYTRARFQBYI","created_at":"2026-07-05T02:09:38.288482+00:00"},{"alias_kind":"pith_short_8","alias_value":"MLQF2QYT","created_at":"2026-07-05T02:09:38.288482+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/MLQF2QYTRARFQBYI5TJYY27HV5","json":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5.json","graph_json":"https://pith.science/api/pith-number/MLQF2QYTRARFQBYI5TJYY27HV5/graph.json","events_json":"https://pith.science/api/pith-number/MLQF2QYTRARFQBYI5TJYY27HV5/events.json","paper":"https://pith.science/paper/MLQF2QYT"},"agent_actions":{"view_html":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5","download_json":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5.json","view_paper":"https://pith.science/paper/MLQF2QYT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2004.05887&json=true","fetch_graph":"https://pith.science/api/pith-number/MLQF2QYTRARFQBYI5TJYY27HV5/graph.json","fetch_events":"https://pith.science/api/pith-number/MLQF2QYTRARFQBYI5TJYY27HV5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5/action/storage_attestation","attest_author":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5/action/author_attestation","sign_citation":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5/action/citation_signature","submit_replication":"https://pith.science/pith/MLQF2QYTRARFQBYI5TJYY27HV5/action/replication_record"}},"created_at":"2026-07-05T02:09:38.288482+00:00","updated_at":"2026-07-05T02:09:38.288482+00:00"}