{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:ZPVUMYQ65QFHQVTLUWYKUIBLJI","short_pith_number":"pith:ZPVUMYQ6","canonical_record":{"source":{"id":"2208.09339","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T13:43:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8854fdb19b66a79c5b8f24597d77e7ec86f1ca37294651a196a1e97794062ce7","abstract_canon_sha256":"a3d18f2a974efaba9cb3612616e9f2dbbfc9c0751ce312d8fcaf04b42785ce11"},"schema_version":"1.0"},"canonical_sha256":"cbeb46621eec0a78566ba5b0aa202b4a1ce452b550df5812990a0a20f38a2948","source":{"kind":"arxiv","id":"2208.09339","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.09339","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"arxiv_version","alias_value":"2208.09339v2","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.09339","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"pith_short_12","alias_value":"ZPVUMYQ65QFH","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"pith_short_16","alias_value":"ZPVUMYQ65QFHQVTL","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"pith_short_8","alias_value":"ZPVUMYQ6","created_at":"2026-07-05T05:33:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:ZPVUMYQ65QFHQVTLUWYKUIBLJI","target":"record","payload":{"canonical_record":{"source":{"id":"2208.09339","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T13:43:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8854fdb19b66a79c5b8f24597d77e7ec86f1ca37294651a196a1e97794062ce7","abstract_canon_sha256":"a3d18f2a974efaba9cb3612616e9f2dbbfc9c0751ce312d8fcaf04b42785ce11"},"schema_version":"1.0"},"canonical_sha256":"cbeb46621eec0a78566ba5b0aa202b4a1ce452b550df5812990a0a20f38a2948","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:33:16.722645Z","signature_b64":"2OH5lEl0uOsUyQQHVFKl0+1k8RXAPItV8H4w66pJN/jb8At++JPK6Bm9DYpq7iJJKxAEbd5D/FpGq3hgRcwVDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cbeb46621eec0a78566ba5b0aa202b4a1ce452b550df5812990a0a20f38a2948","last_reissued_at":"2026-07-05T05:33:16.722086Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:33:16.722086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.09339","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":"2026-07-05T05:33:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l53ICch1mvUOnfZ+LljAgjGl4Idw4dCD8oMTJBmPm01wYX7QjqE7WT6dVwI5VLWkoOI6R33VG4tVu+GEdh5/Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T04:17:25.467878Z"},"content_sha256":"125d33430fa4bb9b52c0a691e7fb8fb8e2e058dd2367aff0b265f4994c2cb518","schema_version":"1.0","event_id":"sha256:125d33430fa4bb9b52c0a691e7fb8fb8e2e058dd2367aff0b265f4994c2cb518"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:ZPVUMYQ65QFHQVTLUWYKUIBLJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating Explainability for Graph Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik, Owen Queen","submitted_at":"2022-08-19T13:43:52Z","abstract_excerpt":"As post hoc explanations are increasingly used to understand the behavior of graph neural networks (GNNs), it becomes crucial to evaluate the quality and reliability of GNN explanations. However, assessing the quality of GNN explanations is challenging as existing graph datasets have no or unreliable ground-truth explanations for a given task. Here, we introduce a synthetic graph data generator, ShapeGGen, which can generate a variety of benchmark datasets (e.g., varying graph sizes, degree distributions, homophilic vs. heterophilic graphs) accompanied by ground-truth explanations. Further, th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.09339","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/2208.09339/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":"2026-07-05T05:33:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UxraaEd8SSaT/UYPcz3o95pqcTzhTkDj9mFO+Q1PY0XCQ9xjwFvYj0/VXKhRN7J2h7RqJ7fv1dHP5aMR9wDODQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T04:17:25.468372Z"},"content_sha256":"5779afff70701b12c74b4dfc0a82f28638c175fe9c388089ca73dc82e08ae052","schema_version":"1.0","event_id":"sha256:5779afff70701b12c74b4dfc0a82f28638c175fe9c388089ca73dc82e08ae052"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI/bundle.json","state_url":"https://pith.science/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI/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":"2026-08-24T04:17:25Z","links":{"resolver":"https://pith.science/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI","bundle":"https://pith.science/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI/bundle.json","state":"https://pith.science/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZPVUMYQ65QFHQVTLUWYKUIBLJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ZPVUMYQ65QFHQVTLUWYKUIBLJI","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":"a3d18f2a974efaba9cb3612616e9f2dbbfc9c0751ce312d8fcaf04b42785ce11","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T13:43:52Z","title_canon_sha256":"8854fdb19b66a79c5b8f24597d77e7ec86f1ca37294651a196a1e97794062ce7"},"schema_version":"1.0","source":{"id":"2208.09339","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.09339","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"arxiv_version","alias_value":"2208.09339v2","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.09339","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"pith_short_12","alias_value":"ZPVUMYQ65QFH","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"pith_short_16","alias_value":"ZPVUMYQ65QFHQVTL","created_at":"2026-07-05T05:33:16Z"},{"alias_kind":"pith_short_8","alias_value":"ZPVUMYQ6","created_at":"2026-07-05T05:33:16Z"}],"graph_snapshots":[{"event_id":"sha256:5779afff70701b12c74b4dfc0a82f28638c175fe9c388089ca73dc82e08ae052","target":"graph","created_at":"2026-07-05T05:33:16Z","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/2208.09339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As post hoc explanations are increasingly used to understand the behavior of graph neural networks (GNNs), it becomes crucial to evaluate the quality and reliability of GNN explanations. However, assessing the quality of GNN explanations is challenging as existing graph datasets have no or unreliable ground-truth explanations for a given task. Here, we introduce a synthetic graph data generator, ShapeGGen, which can generate a variety of benchmark datasets (e.g., varying graph sizes, degree distributions, homophilic vs. heterophilic graphs) accompanied by ground-truth explanations. Further, th","authors_text":"Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik, Owen Queen","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T13:43:52Z","title":"Evaluating Explainability for Graph Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.09339","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":"sha256:125d33430fa4bb9b52c0a691e7fb8fb8e2e058dd2367aff0b265f4994c2cb518","target":"record","created_at":"2026-07-05T05:33:16Z","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":"a3d18f2a974efaba9cb3612616e9f2dbbfc9c0751ce312d8fcaf04b42785ce11","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-08-19T13:43:52Z","title_canon_sha256":"8854fdb19b66a79c5b8f24597d77e7ec86f1ca37294651a196a1e97794062ce7"},"schema_version":"1.0","source":{"id":"2208.09339","kind":"arxiv","version":2}},"canonical_sha256":"cbeb46621eec0a78566ba5b0aa202b4a1ce452b550df5812990a0a20f38a2948","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cbeb46621eec0a78566ba5b0aa202b4a1ce452b550df5812990a0a20f38a2948","first_computed_at":"2026-07-05T05:33:16.722086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:33:16.722086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2OH5lEl0uOsUyQQHVFKl0+1k8RXAPItV8H4w66pJN/jb8At++JPK6Bm9DYpq7iJJKxAEbd5D/FpGq3hgRcwVDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:33:16.722645Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.09339","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:125d33430fa4bb9b52c0a691e7fb8fb8e2e058dd2367aff0b265f4994c2cb518","sha256:5779afff70701b12c74b4dfc0a82f28638c175fe9c388089ca73dc82e08ae052"],"state_sha256":"930d8a69bc77c3f6e086b34d3e520c012aaaf0261c5a64cce162b44f4cc752c6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZqcgZRdtjPqnsyOmVFpM2PUs8crVa7v/PjX0rhAtAYIUU7nbxYAaOEsM+YEbAgb8L++PY3y2cmwcmwkn+qTzBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-24T04:17:25.472332Z","bundle_sha256":"8c42ea34ce15fc32f2bbe9deb3be454a9b611ef929cac05c71516003e89d1e4d"}}