{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:3LA5VQRJYLJOW3ABJGDTYRI6V6","short_pith_number":"pith:3LA5VQRJ","canonical_record":{"source":{"id":"2210.01002","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-03T15:10:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"82c7c806727a8bd9d46ae694e09cb4a09703e688a8c2d25b3096ba253a4568c5","abstract_canon_sha256":"928f344bd5fbfb260f72cb8cc7dd6e5bb7e31917c1151551fab9a8dbdad39ac0"},"schema_version":"1.0"},"canonical_sha256":"dac1dac229c2d2eb6c0149873c451eafae15f0bf80a82cf535ad82720a43bdf1","source":{"kind":"arxiv","id":"2210.01002","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.01002","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"arxiv_version","alias_value":"2210.01002v1","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.01002","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"pith_short_12","alias_value":"3LA5VQRJYLJO","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"pith_short_16","alias_value":"3LA5VQRJYLJOW3AB","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"pith_short_8","alias_value":"3LA5VQRJ","created_at":"2026-07-05T05:02:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:3LA5VQRJYLJOW3ABJGDTYRI6V6","target":"record","payload":{"canonical_record":{"source":{"id":"2210.01002","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-03T15:10:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"82c7c806727a8bd9d46ae694e09cb4a09703e688a8c2d25b3096ba253a4568c5","abstract_canon_sha256":"928f344bd5fbfb260f72cb8cc7dd6e5bb7e31917c1151551fab9a8dbdad39ac0"},"schema_version":"1.0"},"canonical_sha256":"dac1dac229c2d2eb6c0149873c451eafae15f0bf80a82cf535ad82720a43bdf1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:02:50.089812Z","signature_b64":"/PC2g6Px6veTgD8D4o6eZrj8/6OtWXPcJUVsLCVmjTUxATRAoNSyeg0UEtNKP/vIKWWiSL3gZpPlmMKvEbJWBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dac1dac229c2d2eb6c0149873c451eafae15f0bf80a82cf535ad82720a43bdf1","last_reissued_at":"2026-07-05T05:02:50.089398Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:02:50.089398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.01002","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":"2026-07-05T05:02:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ccy5vaeG2lJcEvonNXEfLM0uUE9+FAYpKXDSQI/g1c03eCqumlBMaBGRnsCMJpaLhrvBZ3lABQP7f9Wjd+Y3CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T09:44:46.153100Z"},"content_sha256":"fbee5204942e6683229fcc4aa1d52bf9855fa13adb8fc02e3db7cc0c2c994c65","schema_version":"1.0","event_id":"sha256:fbee5204942e6683229fcc4aa1d52bf9855fa13adb8fc02e3db7cc0c2c994c65"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:3LA5VQRJYLJOW3ABJGDTYRI6V6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ASGNN: Graph Neural Networks with Adaptive Structure","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Songtao Lu, Zengfeng Huang, Zepeng Zhang, Ziping Zhao","submitted_at":"2022-10-03T15:10:40Z","abstract_excerpt":"The graph neural network (GNN) models have presented impressive achievements in numerous machine learning tasks. However, many existing GNN models are shown to be vulnerable to adversarial attacks, which creates a stringent need to build robust GNN architectures. In this work, we propose a novel interpretable message passing scheme with adaptive structure (ASMP) to defend against adversarial attacks on graph structure. Layers in ASMP are derived based on optimization steps that minimize an objective function that learns the node feature and the graph structure simultaneously. ASMP is adaptive "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.01002","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/2210.01002/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":"2026-07-05T05:02:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0QVf9LyownpuIHObeL4Zn4AC+waW+a9f4Aapgbw1ZYp+xYo6oQ1xaLk3CIN55IhtrFcCZ7wsi5NhEzbI21I4CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T09:44:46.154069Z"},"content_sha256":"8a5cc26a1667a9e490cc51581fae1c6ed06651436ba7cd00c2dad6236c0a1118","schema_version":"1.0","event_id":"sha256:8a5cc26a1667a9e490cc51581fae1c6ed06651436ba7cd00c2dad6236c0a1118"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6/bundle.json","state_url":"https://pith.science/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6/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":"2026-08-13T09:44:46Z","links":{"resolver":"https://pith.science/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6","bundle":"https://pith.science/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6/bundle.json","state":"https://pith.science/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3LA5VQRJYLJOW3ABJGDTYRI6V6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:3LA5VQRJYLJOW3ABJGDTYRI6V6","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":"928f344bd5fbfb260f72cb8cc7dd6e5bb7e31917c1151551fab9a8dbdad39ac0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-03T15:10:40Z","title_canon_sha256":"82c7c806727a8bd9d46ae694e09cb4a09703e688a8c2d25b3096ba253a4568c5"},"schema_version":"1.0","source":{"id":"2210.01002","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.01002","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"arxiv_version","alias_value":"2210.01002v1","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.01002","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"pith_short_12","alias_value":"3LA5VQRJYLJO","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"pith_short_16","alias_value":"3LA5VQRJYLJOW3AB","created_at":"2026-07-05T05:02:50Z"},{"alias_kind":"pith_short_8","alias_value":"3LA5VQRJ","created_at":"2026-07-05T05:02:50Z"}],"graph_snapshots":[{"event_id":"sha256:8a5cc26a1667a9e490cc51581fae1c6ed06651436ba7cd00c2dad6236c0a1118","target":"graph","created_at":"2026-07-05T05:02:50Z","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/2210.01002/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The graph neural network (GNN) models have presented impressive achievements in numerous machine learning tasks. However, many existing GNN models are shown to be vulnerable to adversarial attacks, which creates a stringent need to build robust GNN architectures. In this work, we propose a novel interpretable message passing scheme with adaptive structure (ASMP) to defend against adversarial attacks on graph structure. Layers in ASMP are derived based on optimization steps that minimize an objective function that learns the node feature and the graph structure simultaneously. ASMP is adaptive ","authors_text":"Songtao Lu, Zengfeng Huang, Zepeng Zhang, Ziping Zhao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-03T15:10:40Z","title":"ASGNN: Graph Neural Networks with Adaptive Structure"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.01002","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:fbee5204942e6683229fcc4aa1d52bf9855fa13adb8fc02e3db7cc0c2c994c65","target":"record","created_at":"2026-07-05T05:02:50Z","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":"928f344bd5fbfb260f72cb8cc7dd6e5bb7e31917c1151551fab9a8dbdad39ac0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-03T15:10:40Z","title_canon_sha256":"82c7c806727a8bd9d46ae694e09cb4a09703e688a8c2d25b3096ba253a4568c5"},"schema_version":"1.0","source":{"id":"2210.01002","kind":"arxiv","version":1}},"canonical_sha256":"dac1dac229c2d2eb6c0149873c451eafae15f0bf80a82cf535ad82720a43bdf1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dac1dac229c2d2eb6c0149873c451eafae15f0bf80a82cf535ad82720a43bdf1","first_computed_at":"2026-07-05T05:02:50.089398Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:02:50.089398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/PC2g6Px6veTgD8D4o6eZrj8/6OtWXPcJUVsLCVmjTUxATRAoNSyeg0UEtNKP/vIKWWiSL3gZpPlmMKvEbJWBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:02:50.089812Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.01002","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbee5204942e6683229fcc4aa1d52bf9855fa13adb8fc02e3db7cc0c2c994c65","sha256:8a5cc26a1667a9e490cc51581fae1c6ed06651436ba7cd00c2dad6236c0a1118"],"state_sha256":"9f68905074c789eb2c186828b8d1e6d856165bef6f0c669a7824fa60727380ea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5SPt9w/bkix2Qu7QfLNDspJTkiVBFw9IZZT0KlQcUyLF0ZRc1tW1lKMyPXkHaMRcnYhI7eupbCApBIpUewtBAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T09:44:46.164141Z","bundle_sha256":"a0dcb6e28d9c75d2201c08d0812ff0c026ed42394541bb7b31519d83e9a1b86d"}}