{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WMUZ75KF4VM6O4UFIC3BNU43JX","short_pith_number":"pith:WMUZ75KF","canonical_record":{"source":{"id":"2406.03193","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-05T12:23:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8b3755322dc8564130234756dfa95965b5cdf6757ff8f91b39b732fb04a4e6d6","abstract_canon_sha256":"2308200f33cc41136684a99636f334484ac934453c4c7fcc87fa7be84d946a20"},"schema_version":"1.0"},"canonical_sha256":"b3299ff545e559e7728540b616d39b4de72caeb7acae34e65e03038eb2ae6d1b","source":{"kind":"arxiv","id":"2406.03193","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.03193","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"arxiv_version","alias_value":"2406.03193v1","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.03193","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"pith_short_12","alias_value":"WMUZ75KF4VM6","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"pith_short_16","alias_value":"WMUZ75KF4VM6O4UF","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"pith_short_8","alias_value":"WMUZ75KF","created_at":"2026-07-05T08:27:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WMUZ75KF4VM6O4UFIC3BNU43JX","target":"record","payload":{"canonical_record":{"source":{"id":"2406.03193","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-05T12:23:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8b3755322dc8564130234756dfa95965b5cdf6757ff8f91b39b732fb04a4e6d6","abstract_canon_sha256":"2308200f33cc41136684a99636f334484ac934453c4c7fcc87fa7be84d946a20"},"schema_version":"1.0"},"canonical_sha256":"b3299ff545e559e7728540b616d39b4de72caeb7acae34e65e03038eb2ae6d1b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:27:52.784197Z","signature_b64":"05SGHlFSQKphYfK58nZtY5XoWezEGPceGQ6Qyc35E9m5nbDxa9mPk+3I4NM4LBr9F0IRPmjkrrZYgBVxqP0fDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3299ff545e559e7728540b616d39b4de72caeb7acae34e65e03038eb2ae6d1b","last_reissued_at":"2026-07-05T08:27:52.783675Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:27:52.783675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.03193","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":"2026-07-05T08:27:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t/Y3dzBI+vhTb75EUJddg42ijji4KEf7cHlhJa+DLCCjsngx9lA4nfBLFdrVJiDjL8Abv5mSZI64SZ3xv7q+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:15:38.105471Z"},"content_sha256":"e2eb477fa9b50be9ea9756cb976bc6ef420e687e67ad9d1f7bbe84f97ae398f8","schema_version":"1.0","event_id":"sha256:e2eb477fa9b50be9ea9756cb976bc6ef420e687e67ad9d1f7bbe84f97ae398f8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WMUZ75KF4VM6O4UFIC3BNU43JX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph Neural Network Explanations are Fragile","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Binghui Wang, Jiate Li, Jinyuan Jia, Meng Pang, Yun Dong","submitted_at":"2024-06-05T12:23:02Z","abstract_excerpt":"Explainable Graph Neural Network (GNN) has emerged recently to foster the trust of using GNNs. Existing GNN explainers are developed from various perspectives to enhance the explanation performance. We take the first step to study GNN explainers under adversarial attack--We found that an adversary slightly perturbing graph structure can ensure GNN model makes correct predictions, but the GNN explainer yields a drastically different explanation on the perturbed graph. Specifically, we first formulate the attack problem under a practical threat model (i.e., the adversary has limited knowledge ab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.03193","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/2406.03193/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":"2026-07-05T08:27:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NT9TdfGdRBqzpjU9q9rjr+gJMegejQ1vQ0ZHseZ2XHRfztCMJxuJs/BzMTl1fGazo25egI4sf7euD33+1LQTAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:15:38.105997Z"},"content_sha256":"70cae82b72818fc22dd87ab1a81366a59f7bb4896a0e8c61f957fb11a325b93e","schema_version":"1.0","event_id":"sha256:70cae82b72818fc22dd87ab1a81366a59f7bb4896a0e8c61f957fb11a325b93e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WMUZ75KF4VM6O4UFIC3BNU43JX/bundle.json","state_url":"https://pith.science/pith/WMUZ75KF4VM6O4UFIC3BNU43JX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WMUZ75KF4VM6O4UFIC3BNU43JX/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":"2026-08-06T15:15:38Z","links":{"resolver":"https://pith.science/pith/WMUZ75KF4VM6O4UFIC3BNU43JX","bundle":"https://pith.science/pith/WMUZ75KF4VM6O4UFIC3BNU43JX/bundle.json","state":"https://pith.science/pith/WMUZ75KF4VM6O4UFIC3BNU43JX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WMUZ75KF4VM6O4UFIC3BNU43JX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WMUZ75KF4VM6O4UFIC3BNU43JX","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":"2308200f33cc41136684a99636f334484ac934453c4c7fcc87fa7be84d946a20","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-05T12:23:02Z","title_canon_sha256":"8b3755322dc8564130234756dfa95965b5cdf6757ff8f91b39b732fb04a4e6d6"},"schema_version":"1.0","source":{"id":"2406.03193","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.03193","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"arxiv_version","alias_value":"2406.03193v1","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.03193","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"pith_short_12","alias_value":"WMUZ75KF4VM6","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"pith_short_16","alias_value":"WMUZ75KF4VM6O4UF","created_at":"2026-07-05T08:27:52Z"},{"alias_kind":"pith_short_8","alias_value":"WMUZ75KF","created_at":"2026-07-05T08:27:52Z"}],"graph_snapshots":[{"event_id":"sha256:70cae82b72818fc22dd87ab1a81366a59f7bb4896a0e8c61f957fb11a325b93e","target":"graph","created_at":"2026-07-05T08:27:52Z","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/2406.03193/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Explainable Graph Neural Network (GNN) has emerged recently to foster the trust of using GNNs. Existing GNN explainers are developed from various perspectives to enhance the explanation performance. We take the first step to study GNN explainers under adversarial attack--We found that an adversary slightly perturbing graph structure can ensure GNN model makes correct predictions, but the GNN explainer yields a drastically different explanation on the perturbed graph. Specifically, we first formulate the attack problem under a practical threat model (i.e., the adversary has limited knowledge ab","authors_text":"Binghui Wang, Jiate Li, Jinyuan Jia, Meng Pang, Yun Dong","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-05T12:23:02Z","title":"Graph Neural Network Explanations are Fragile"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.03193","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:e2eb477fa9b50be9ea9756cb976bc6ef420e687e67ad9d1f7bbe84f97ae398f8","target":"record","created_at":"2026-07-05T08:27:52Z","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":"2308200f33cc41136684a99636f334484ac934453c4c7fcc87fa7be84d946a20","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-06-05T12:23:02Z","title_canon_sha256":"8b3755322dc8564130234756dfa95965b5cdf6757ff8f91b39b732fb04a4e6d6"},"schema_version":"1.0","source":{"id":"2406.03193","kind":"arxiv","version":1}},"canonical_sha256":"b3299ff545e559e7728540b616d39b4de72caeb7acae34e65e03038eb2ae6d1b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3299ff545e559e7728540b616d39b4de72caeb7acae34e65e03038eb2ae6d1b","first_computed_at":"2026-07-05T08:27:52.783675Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:27:52.783675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"05SGHlFSQKphYfK58nZtY5XoWezEGPceGQ6Qyc35E9m5nbDxa9mPk+3I4NM4LBr9F0IRPmjkrrZYgBVxqP0fDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:27:52.784197Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.03193","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e2eb477fa9b50be9ea9756cb976bc6ef420e687e67ad9d1f7bbe84f97ae398f8","sha256:70cae82b72818fc22dd87ab1a81366a59f7bb4896a0e8c61f957fb11a325b93e"],"state_sha256":"f0895406ccd52751b3165803455c115ee21bea718f21ec8fb23c9fbe8666a506"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9EYaWb7pVyJPjGBDP8tvV6c02rGg7NekjFVZ/qqfe3r+um+rWFoN9mR4lpEuRoRK0eD4GcHEhn2IJ4WXTfsOCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T15:15:38.120388Z","bundle_sha256":"acb0e40a374bef18b45212a6e0667eddd41f5b76568a72a0776c8c4f5084795f"}}