{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7UUXQWL7FZMP7EYAFKXIF47Q7Y","short_pith_number":"pith:7UUXQWL7","canonical_record":{"source":{"id":"2405.03004","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-05-05T17:19:35Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"629b9fc9ad0a07c5545a92e4faeb03c3b75c1d2d85fcf0457545fc1679d9f937","abstract_canon_sha256":"a8ada24a699048f322d7d1ef651e968b025930bf0259934daac6639c3a7eeec8"},"schema_version":"1.0"},"canonical_sha256":"fd2978597f2e58ff93002aae82f3f0fe1c9e11c6414b3142ba36356791ac5ddb","source":{"kind":"arxiv","id":"2405.03004","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03004","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03004v1","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03004","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_12","alias_value":"7UUXQWL7FZMP","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_16","alias_value":"7UUXQWL7FZMP7EYA","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_8","alias_value":"7UUXQWL7","created_at":"2026-07-05T08:15:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7UUXQWL7FZMP7EYAFKXIF47Q7Y","target":"record","payload":{"canonical_record":{"source":{"id":"2405.03004","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-05-05T17:19:35Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"629b9fc9ad0a07c5545a92e4faeb03c3b75c1d2d85fcf0457545fc1679d9f937","abstract_canon_sha256":"a8ada24a699048f322d7d1ef651e968b025930bf0259934daac6639c3a7eeec8"},"schema_version":"1.0"},"canonical_sha256":"fd2978597f2e58ff93002aae82f3f0fe1c9e11c6414b3142ba36356791ac5ddb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:15:57.166132Z","signature_b64":"jETlDDrrI3FuShVclsblCtb8BDv9F0YGXcMb8UR4dFXDTbvznC5RuRvOfSIj8v6VPnijQ/MAiNIAg4dqx/63DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fd2978597f2e58ff93002aae82f3f0fe1c9e11c6414b3142ba36356791ac5ddb","last_reissued_at":"2026-07-05T08:15:57.165699Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:15:57.165699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.03004","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":"2026-07-05T08:15:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zTvxWT/CC5qYDML29XzuAp1TVun53j0GVVKCT6wH1yrnShTK4M1Ea2EKqbLz0BRU7fdYIp6vXW1ht2brD+AUDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T13:14:34.565509Z"},"content_sha256":"73408f066c91eb377d7788a5d7d1ac97b73e86c5e027517b39b43b86e2c98141","schema_version":"1.0","event_id":"sha256:73408f066c91eb377d7788a5d7d1ac97b73e86c5e027517b39b43b86e2c98141"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7UUXQWL7FZMP7EYAFKXIF47Q7Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring prompts to elicit memorization in masked language model-based named entity recognition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Anastasiia Sedova, Benjamin Roth, Lisa Nu{\\ss}baumer, Pedro Henrique Luz de Araujo, Vasiliki Kougia, Yuxi Xia","submitted_at":"2024-05-05T17:19:35Z","abstract_excerpt":"Training data memorization in language models impacts model capability (generalization) and safety (privacy risk). This paper focuses on analyzing prompts' impact on detecting the memorization of 6 masked language model-based named entity recognition models. Specifically, we employ a diverse set of 400 automatically generated prompts, and a pairwise dataset where each pair consists of one person's name from the training set and another name out of the set. A prompt completed with a person's name serves as input for getting the model's confidence in predicting this name. Finally, the prompt per"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03004","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/2405.03004/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":"2026-07-05T08:15:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0gt2ZfVoG6/xPZPnbq3IgxEPSfErJPjfWJHxEiLvyVW5PYXyhdd/J/TbyrUBDfRcfHDo1zDcom01n+YW1Ds1Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T13:14:34.566024Z"},"content_sha256":"2d43671c7a8062060159d5afa0f5f630264c1f7603fea60a9a7ad02eecd62a38","schema_version":"1.0","event_id":"sha256:2d43671c7a8062060159d5afa0f5f630264c1f7603fea60a9a7ad02eecd62a38"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y/bundle.json","state_url":"https://pith.science/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y/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":"2026-08-21T13:14:34Z","links":{"resolver":"https://pith.science/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y","bundle":"https://pith.science/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y/bundle.json","state":"https://pith.science/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7UUXQWL7FZMP7EYAFKXIF47Q7Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7UUXQWL7FZMP7EYAFKXIF47Q7Y","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":"a8ada24a699048f322d7d1ef651e968b025930bf0259934daac6639c3a7eeec8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-05-05T17:19:35Z","title_canon_sha256":"629b9fc9ad0a07c5545a92e4faeb03c3b75c1d2d85fcf0457545fc1679d9f937"},"schema_version":"1.0","source":{"id":"2405.03004","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03004","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03004v1","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03004","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_12","alias_value":"7UUXQWL7FZMP","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_16","alias_value":"7UUXQWL7FZMP7EYA","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_8","alias_value":"7UUXQWL7","created_at":"2026-07-05T08:15:57Z"}],"graph_snapshots":[{"event_id":"sha256:2d43671c7a8062060159d5afa0f5f630264c1f7603fea60a9a7ad02eecd62a38","target":"graph","created_at":"2026-07-05T08:15:57Z","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/2405.03004/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training data memorization in language models impacts model capability (generalization) and safety (privacy risk). This paper focuses on analyzing prompts' impact on detecting the memorization of 6 masked language model-based named entity recognition models. Specifically, we employ a diverse set of 400 automatically generated prompts, and a pairwise dataset where each pair consists of one person's name from the training set and another name out of the set. A prompt completed with a person's name serves as input for getting the model's confidence in predicting this name. Finally, the prompt per","authors_text":"Anastasiia Sedova, Benjamin Roth, Lisa Nu{\\ss}baumer, Pedro Henrique Luz de Araujo, Vasiliki Kougia, Yuxi Xia","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-05-05T17:19:35Z","title":"Exploring prompts to elicit memorization in masked language model-based named entity recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03004","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":"sha256:73408f066c91eb377d7788a5d7d1ac97b73e86c5e027517b39b43b86e2c98141","target":"record","created_at":"2026-07-05T08:15:57Z","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":"a8ada24a699048f322d7d1ef651e968b025930bf0259934daac6639c3a7eeec8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-05-05T17:19:35Z","title_canon_sha256":"629b9fc9ad0a07c5545a92e4faeb03c3b75c1d2d85fcf0457545fc1679d9f937"},"schema_version":"1.0","source":{"id":"2405.03004","kind":"arxiv","version":1}},"canonical_sha256":"fd2978597f2e58ff93002aae82f3f0fe1c9e11c6414b3142ba36356791ac5ddb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fd2978597f2e58ff93002aae82f3f0fe1c9e11c6414b3142ba36356791ac5ddb","first_computed_at":"2026-07-05T08:15:57.165699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:15:57.165699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jETlDDrrI3FuShVclsblCtb8BDv9F0YGXcMb8UR4dFXDTbvznC5RuRvOfSIj8v6VPnijQ/MAiNIAg4dqx/63DA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:15:57.166132Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.03004","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:73408f066c91eb377d7788a5d7d1ac97b73e86c5e027517b39b43b86e2c98141","sha256:2d43671c7a8062060159d5afa0f5f630264c1f7603fea60a9a7ad02eecd62a38"],"state_sha256":"9d482b9d7404a9e83216d31efea3edd2d1f97d1ba9f2d5f07fc68888fa74d631"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IEfPhBnWTe+nbhydG9ZfXcHJL9yrR6PxMkpbqSjVcxWLwr1gpoxNpiRdyxOfeD5mSbtDb48l8TCf0lIOEnC2Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T13:14:34.570622Z","bundle_sha256":"93d3bcb022ca05fccaf8dc5f74391c865d7a6d28e0131a2dc72a8ea3ce4437ff"}}