{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:X32BGHUGR6ORFTMFG5RKT5ZN4X","short_pith_number":"pith:X32BGHUG","canonical_record":{"source":{"id":"2407.14206","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T11:04:54Z","cross_cats_sorted":[],"title_canon_sha256":"446847e9eb0daec12a5aefac88225ff308806fb2534943a5efb9ae29f3aad6f8","abstract_canon_sha256":"8d3e4364d577cb92d2e0f873db4f5e9423ad664fb8a394a2ee1e42e3e919c3f0"},"schema_version":"1.0"},"canonical_sha256":"bef4131e868f9d12cd853762a9f72de5c11a1e4a59dbfa0112e387bcd4a19ea7","source":{"kind":"arxiv","id":"2407.14206","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.14206","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"arxiv_version","alias_value":"2407.14206v2","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.14206","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"pith_short_12","alias_value":"X32BGHUGR6OR","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"pith_short_16","alias_value":"X32BGHUGR6ORFTMF","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"pith_short_8","alias_value":"X32BGHUG","created_at":"2026-07-05T10:09:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:X32BGHUGR6ORFTMFG5RKT5ZN4X","target":"record","payload":{"canonical_record":{"source":{"id":"2407.14206","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T11:04:54Z","cross_cats_sorted":[],"title_canon_sha256":"446847e9eb0daec12a5aefac88225ff308806fb2534943a5efb9ae29f3aad6f8","abstract_canon_sha256":"8d3e4364d577cb92d2e0f873db4f5e9423ad664fb8a394a2ee1e42e3e919c3f0"},"schema_version":"1.0"},"canonical_sha256":"bef4131e868f9d12cd853762a9f72de5c11a1e4a59dbfa0112e387bcd4a19ea7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:45.602086Z","signature_b64":"iI8967R9mfXBpFUZ4M7r8HQl4nKi1EIzQ62Mgn2XbHjPO2U2vsHGp6qTnOZyu5quQB0hJKuS/g8Rc3W09WGLAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bef4131e868f9d12cd853762a9f72de5c11a1e4a59dbfa0112e387bcd4a19ea7","last_reissued_at":"2026-07-05T10:09:45.601614Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:45.601614Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.14206","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":"2026-07-05T10:09:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xIKhfqDuL3YbwyMAIrLgzzSDx+gd7f5bzZS8TGpgQ/+gX6V/TtK6byJpr0HpDceH3tkV6GUY0he/i74TnxoMDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:31:46.409377Z"},"content_sha256":"3925e203d17a0236a871e41b46ec0344ed5152f89bc2aee48d647cbea5d6fddb","schema_version":"1.0","event_id":"sha256:3925e203d17a0236a871e41b46ec0344ed5152f89bc2aee48d647cbea5d6fddb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:X32BGHUGR6ORFTMFG5RKT5ZN4X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Watermark Smoothing Attacks against Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Hamed Hassani, Hongyan Chang, Reza Shokri","submitted_at":"2024-07-19T11:04:54Z","abstract_excerpt":"Watermarking is a key technique for detecting AI-generated text. In this work, we study its vulnerabilities and introduce the Smoothing Attack, a novel watermark removal method. By leveraging the relationship between the model's confidence and watermark detectability, our attack selectively smoothes the watermarked content, erasing watermark traces while preserving text quality. We validate our attack on open-source models ranging from $1.3$B to $30$B parameters on $10$ different watermarks, demonstrating its effectiveness. Our findings expose critical weaknesses in existing watermarking schem"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.14206","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/2407.14206/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":"2026-07-05T10:09:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FXTIUJFMnoq64V28G01frHybtHSr1da2lmX4C5p2QB/XmHMSnlnhO6drD/iNUIWEWfgRXei3Hlx8/3rTDAXbDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:31:46.410400Z"},"content_sha256":"da78926074cc1ce00408f46c4270195a2e34c7a5ebdcdcc04ceacd1cdcd13d38","schema_version":"1.0","event_id":"sha256:da78926074cc1ce00408f46c4270195a2e34c7a5ebdcdcc04ceacd1cdcd13d38"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X/bundle.json","state_url":"https://pith.science/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X/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":"2026-08-05T23:31:46Z","links":{"resolver":"https://pith.science/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X","bundle":"https://pith.science/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X/bundle.json","state":"https://pith.science/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X32BGHUGR6ORFTMFG5RKT5ZN4X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:X32BGHUGR6ORFTMFG5RKT5ZN4X","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":"8d3e4364d577cb92d2e0f873db4f5e9423ad664fb8a394a2ee1e42e3e919c3f0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T11:04:54Z","title_canon_sha256":"446847e9eb0daec12a5aefac88225ff308806fb2534943a5efb9ae29f3aad6f8"},"schema_version":"1.0","source":{"id":"2407.14206","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.14206","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"arxiv_version","alias_value":"2407.14206v2","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.14206","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"pith_short_12","alias_value":"X32BGHUGR6OR","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"pith_short_16","alias_value":"X32BGHUGR6ORFTMF","created_at":"2026-07-05T10:09:45Z"},{"alias_kind":"pith_short_8","alias_value":"X32BGHUG","created_at":"2026-07-05T10:09:45Z"}],"graph_snapshots":[{"event_id":"sha256:da78926074cc1ce00408f46c4270195a2e34c7a5ebdcdcc04ceacd1cdcd13d38","target":"graph","created_at":"2026-07-05T10:09:45Z","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/2407.14206/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Watermarking is a key technique for detecting AI-generated text. In this work, we study its vulnerabilities and introduce the Smoothing Attack, a novel watermark removal method. By leveraging the relationship between the model's confidence and watermark detectability, our attack selectively smoothes the watermarked content, erasing watermark traces while preserving text quality. We validate our attack on open-source models ranging from $1.3$B to $30$B parameters on $10$ different watermarks, demonstrating its effectiveness. Our findings expose critical weaknesses in existing watermarking schem","authors_text":"Hamed Hassani, Hongyan Chang, Reza Shokri","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T11:04:54Z","title":"Watermark Smoothing Attacks against Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.14206","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":"sha256:3925e203d17a0236a871e41b46ec0344ed5152f89bc2aee48d647cbea5d6fddb","target":"record","created_at":"2026-07-05T10:09:45Z","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":"8d3e4364d577cb92d2e0f873db4f5e9423ad664fb8a394a2ee1e42e3e919c3f0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-19T11:04:54Z","title_canon_sha256":"446847e9eb0daec12a5aefac88225ff308806fb2534943a5efb9ae29f3aad6f8"},"schema_version":"1.0","source":{"id":"2407.14206","kind":"arxiv","version":2}},"canonical_sha256":"bef4131e868f9d12cd853762a9f72de5c11a1e4a59dbfa0112e387bcd4a19ea7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bef4131e868f9d12cd853762a9f72de5c11a1e4a59dbfa0112e387bcd4a19ea7","first_computed_at":"2026-07-05T10:09:45.601614Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:09:45.601614Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iI8967R9mfXBpFUZ4M7r8HQl4nKi1EIzQ62Mgn2XbHjPO2U2vsHGp6qTnOZyu5quQB0hJKuS/g8Rc3W09WGLAg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:09:45.602086Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.14206","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3925e203d17a0236a871e41b46ec0344ed5152f89bc2aee48d647cbea5d6fddb","sha256:da78926074cc1ce00408f46c4270195a2e34c7a5ebdcdcc04ceacd1cdcd13d38"],"state_sha256":"68b362c23e1424b10bb0e711a6009470e7fcd815b4e945e193a839f419555df8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MWikSf28UDXd9Mq2tMqSMXHNduZmatLmJenUYXyFaU5KmTBv92XWcduG8YENiyEyg00Ps3oibpAUj/jpSId/Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T23:31:46.416798Z","bundle_sha256":"d4e0b5e4bebd590fb6f68c118b9a4bb525ae92d067a0a5622d4af13988d7a6a4"}}