{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VYWJ7TFN5TAWEO3MDJDDLAOSXQ","short_pith_number":"pith:VYWJ7TFN","canonical_record":{"source":{"id":"2505.03392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-06T10:15:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"716d08be638c07e6dedb8d5458aa72946dfd77da05c6a84c654e98b1d38ba133","abstract_canon_sha256":"a9db58ec5e88bd78f32878f3f25a003398915946a326c9183ddfb2bf47688996"},"schema_version":"1.0"},"canonical_sha256":"ae2c9fccadecc1623b6c1a463581d2bc36cbb64c10e01601731dfcf19abf850a","source":{"kind":"arxiv","id":"2505.03392","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.03392","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"arxiv_version","alias_value":"2505.03392v1","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.03392","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"pith_short_12","alias_value":"VYWJ7TFN5TAW","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"pith_short_16","alias_value":"VYWJ7TFN5TAWEO3M","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"pith_short_8","alias_value":"VYWJ7TFN","created_at":"2026-07-05T10:59:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VYWJ7TFN5TAWEO3MDJDDLAOSXQ","target":"record","payload":{"canonical_record":{"source":{"id":"2505.03392","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-06T10:15:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"716d08be638c07e6dedb8d5458aa72946dfd77da05c6a84c654e98b1d38ba133","abstract_canon_sha256":"a9db58ec5e88bd78f32878f3f25a003398915946a326c9183ddfb2bf47688996"},"schema_version":"1.0"},"canonical_sha256":"ae2c9fccadecc1623b6c1a463581d2bc36cbb64c10e01601731dfcf19abf850a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:59:15.293283Z","signature_b64":"gA8VXAQrMmKsCJl/AQNxrdJ4ppGwUrw9vIrRmw1jjUyvmWqQaXEQ4McbbGgHhOnr8ymx3eSqohvqyasjvqlFCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae2c9fccadecc1623b6c1a463581d2bc36cbb64c10e01601731dfcf19abf850a","last_reissued_at":"2026-07-05T10:59:15.292800Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:59:15.292800Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.03392","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":"2026-07-05T10:59:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v3JWY4uKyPSgLXtgKYwhDPxXv9kRTf+4qOXpWXxJhSosnuXDi6xjexiegwqteFJGDjlgb7sTalM07SA9BYF/DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T06:34:34.603854Z"},"content_sha256":"ef571851e35d20e068ed771d6001c30807eccc79d2457c5d112c5d6778b35b0f","schema_version":"1.0","event_id":"sha256:ef571851e35d20e068ed771d6001c30807eccc79d2457c5d112c5d6778b35b0f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VYWJ7TFN5TAWEO3MDJDDLAOSXQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatic Calibration for Membership Inference Attack on Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dongxiao Zhu, Hui Zhu, Mohammad Amin Roshani, Prashant Khanduri, Saleh Zare Zade, Xiangyu Zhou, Yao Qiang","submitted_at":"2025-05-06T10:15:05Z","abstract_excerpt":"Membership Inference Attacks (MIAs) have recently been employed to determine whether a specific text was part of the pre-training data of Large Language Models (LLMs). However, existing methods often misinfer non-members as members, leading to a high false positive rate, or depend on additional reference models for probability calibration, which limits their practicality. To overcome these challenges, we introduce a novel framework called Automatic Calibration Membership Inference Attack (ACMIA), which utilizes a tunable temperature to calibrate output probabilities effectively. This approach "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.03392","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/2505.03392/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":"2026-07-05T10:59:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NNSf4Q0yiWT6jvK9IK851F9d3rwnsU4bXZalET6cS31B7vTfg0tnZjMrYAWjjKukSuMksXXch0Mxfpe6ZZpwDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T06:34:34.604216Z"},"content_sha256":"d98eaab3cc21cdb30875f3a7afe724e08d5e4485b8dd09c17a1f65e1ff626d71","schema_version":"1.0","event_id":"sha256:d98eaab3cc21cdb30875f3a7afe724e08d5e4485b8dd09c17a1f65e1ff626d71"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ/bundle.json","state_url":"https://pith.science/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ/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":"2026-07-19T06:34:34Z","links":{"resolver":"https://pith.science/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ","bundle":"https://pith.science/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ/bundle.json","state":"https://pith.science/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VYWJ7TFN5TAWEO3MDJDDLAOSXQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VYWJ7TFN5TAWEO3MDJDDLAOSXQ","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":"a9db58ec5e88bd78f32878f3f25a003398915946a326c9183ddfb2bf47688996","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-06T10:15:05Z","title_canon_sha256":"716d08be638c07e6dedb8d5458aa72946dfd77da05c6a84c654e98b1d38ba133"},"schema_version":"1.0","source":{"id":"2505.03392","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.03392","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"arxiv_version","alias_value":"2505.03392v1","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.03392","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"pith_short_12","alias_value":"VYWJ7TFN5TAW","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"pith_short_16","alias_value":"VYWJ7TFN5TAWEO3M","created_at":"2026-07-05T10:59:15Z"},{"alias_kind":"pith_short_8","alias_value":"VYWJ7TFN","created_at":"2026-07-05T10:59:15Z"}],"graph_snapshots":[{"event_id":"sha256:d98eaab3cc21cdb30875f3a7afe724e08d5e4485b8dd09c17a1f65e1ff626d71","target":"graph","created_at":"2026-07-05T10:59:15Z","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/2505.03392/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Membership Inference Attacks (MIAs) have recently been employed to determine whether a specific text was part of the pre-training data of Large Language Models (LLMs). However, existing methods often misinfer non-members as members, leading to a high false positive rate, or depend on additional reference models for probability calibration, which limits their practicality. To overcome these challenges, we introduce a novel framework called Automatic Calibration Membership Inference Attack (ACMIA), which utilizes a tunable temperature to calibrate output probabilities effectively. This approach ","authors_text":"Dongxiao Zhu, Hui Zhu, Mohammad Amin Roshani, Prashant Khanduri, Saleh Zare Zade, Xiangyu Zhou, Yao Qiang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-06T10:15:05Z","title":"Automatic Calibration for Membership Inference Attack on Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.03392","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:ef571851e35d20e068ed771d6001c30807eccc79d2457c5d112c5d6778b35b0f","target":"record","created_at":"2026-07-05T10:59:15Z","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":"a9db58ec5e88bd78f32878f3f25a003398915946a326c9183ddfb2bf47688996","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-06T10:15:05Z","title_canon_sha256":"716d08be638c07e6dedb8d5458aa72946dfd77da05c6a84c654e98b1d38ba133"},"schema_version":"1.0","source":{"id":"2505.03392","kind":"arxiv","version":1}},"canonical_sha256":"ae2c9fccadecc1623b6c1a463581d2bc36cbb64c10e01601731dfcf19abf850a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae2c9fccadecc1623b6c1a463581d2bc36cbb64c10e01601731dfcf19abf850a","first_computed_at":"2026-07-05T10:59:15.292800Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:59:15.292800Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gA8VXAQrMmKsCJl/AQNxrdJ4ppGwUrw9vIrRmw1jjUyvmWqQaXEQ4McbbGgHhOnr8ymx3eSqohvqyasjvqlFCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:59:15.293283Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.03392","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ef571851e35d20e068ed771d6001c30807eccc79d2457c5d112c5d6778b35b0f","sha256:d98eaab3cc21cdb30875f3a7afe724e08d5e4485b8dd09c17a1f65e1ff626d71"],"state_sha256":"cbb9c8ab059b65fc21b2d0c2592e53d92a947850b53c91d102c484b472257e15"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nhLa4RmtQhTOYOnmtlyjAdn5MerbiQ1sfJC3rmw/8fFyB8FkuknBgezP4ox35mjnw4tDLlXk4yF6ZKthJTRIDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-19T06:34:34.606362Z","bundle_sha256":"60287016c6a88ec35a0d5533453b623e2da527cf06edfa45618cf96c1db7b13f"}}