{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:75JZ7XEMQEBSNGQ267ITZFNV25","short_pith_number":"pith:75JZ7XEM","canonical_record":{"source":{"id":"1906.12269","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-28T15:40:10Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"f2aef535bed3cccb1579cda2a3d01ce246837a6c8b4fc8f7a0187aaf9412ec6f","abstract_canon_sha256":"54660fb9fa77ff2ebe44374b9153aa8451ee69fd975e74568ca99f67b9193ffe"},"schema_version":"1.0"},"canonical_sha256":"ff539fdc8c8103269a1af7d13c95b5d7429ff3746c120f484f1b94090148f1c6","source":{"kind":"arxiv","id":"1906.12269","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.12269","created_at":"2026-05-17T23:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"1906.12269v1","created_at":"2026-05-17T23:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.12269","created_at":"2026-05-17T23:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"75JZ7XEMQEBS","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"75JZ7XEMQEBSNGQ2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"75JZ7XEM","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:75JZ7XEMQEBSNGQ267ITZFNV25","target":"record","payload":{"canonical_record":{"source":{"id":"1906.12269","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-28T15:40:10Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"f2aef535bed3cccb1579cda2a3d01ce246837a6c8b4fc8f7a0187aaf9412ec6f","abstract_canon_sha256":"54660fb9fa77ff2ebe44374b9153aa8451ee69fd975e74568ca99f67b9193ffe"},"schema_version":"1.0"},"canonical_sha256":"ff539fdc8c8103269a1af7d13c95b5d7429ff3746c120f484f1b94090148f1c6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:58.810536Z","signature_b64":"8pe59G7Pfrnczq5EWlcH5CCFFm+TNWLqBQFBygqlivF9hRoEFPwLXi0k+2wp1/KMNkqdFfBOT3lHQKUAqL3pAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff539fdc8c8103269a1af7d13c95b5d7429ff3746c120f484f1b94090148f1c6","last_reissued_at":"2026-05-17T23:41:58.810024Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:58.810024Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.12269","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":"2026-05-17T23:41:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NPCE8eFGTnlcLqAFjxOT+H0itCqQbfw9PPRWQshdNGqlTec95sfCGajNWCpTv3C8cA1AsFQFGkyhgacX8X0TAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T15:25:33.987140Z"},"content_sha256":"65eac8c5fa0e7bb913016762e06849019251865d92603d10a5ed46400deb3c05","schema_version":"1.0","event_id":"sha256:65eac8c5fa0e7bb913016762e06849019251865d92603d10a5ed46400deb3c05"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:75JZ7XEMQEBSNGQ267ITZFNV25","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Certifiable Robustness and Robust Training for Graph Convolutional Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Daniel Z\\\"ugner, Stephan G\\\"unnemann","submitted_at":"2019-06-28T15:40:10Z","abstract_excerpt":"Recent works show that Graph Neural Networks (GNNs) are highly non-robust with respect to adversarial attacks on both the graph structure and the node attributes, making their outcomes unreliable. We propose the first method for certifiable (non-)robustness of graph convolutional networks with respect to perturbations of the node attributes. We consider the case of binary node attributes (e.g. bag-of-words) and perturbations that are L_0-bounded. If a node has been certified with our method, it is guaranteed to be robust under any possible perturbation given the attack model. Likewise, we can "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.12269","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":""},"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":"2026-05-17T23:41:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SPpGGSFmdBRiuYQVCJgcCGDnvruKiKtM0Y4/TMAwV8JEpr7yrxNCa9XIqEhV+Q5dKO/guqnEPEwlxlNZiXbxDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T15:25:33.987502Z"},"content_sha256":"6b54ba89c3f6e854a8d5e16ad0b0fa01763c085f09d381bee0525f9e339b5372","schema_version":"1.0","event_id":"sha256:6b54ba89c3f6e854a8d5e16ad0b0fa01763c085f09d381bee0525f9e339b5372"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/75JZ7XEMQEBSNGQ267ITZFNV25/bundle.json","state_url":"https://pith.science/pith/75JZ7XEMQEBSNGQ267ITZFNV25/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/75JZ7XEMQEBSNGQ267ITZFNV25/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":"2026-06-05T15:25:33Z","links":{"resolver":"https://pith.science/pith/75JZ7XEMQEBSNGQ267ITZFNV25","bundle":"https://pith.science/pith/75JZ7XEMQEBSNGQ267ITZFNV25/bundle.json","state":"https://pith.science/pith/75JZ7XEMQEBSNGQ267ITZFNV25/state.json","well_known_bundle":"https://pith.science/.well-known/pith/75JZ7XEMQEBSNGQ267ITZFNV25/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:75JZ7XEMQEBSNGQ267ITZFNV25","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":"54660fb9fa77ff2ebe44374b9153aa8451ee69fd975e74568ca99f67b9193ffe","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-28T15:40:10Z","title_canon_sha256":"f2aef535bed3cccb1579cda2a3d01ce246837a6c8b4fc8f7a0187aaf9412ec6f"},"schema_version":"1.0","source":{"id":"1906.12269","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.12269","created_at":"2026-05-17T23:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"1906.12269v1","created_at":"2026-05-17T23:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.12269","created_at":"2026-05-17T23:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"75JZ7XEMQEBS","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"75JZ7XEMQEBSNGQ2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"75JZ7XEM","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:6b54ba89c3f6e854a8d5e16ad0b0fa01763c085f09d381bee0525f9e339b5372","target":"graph","created_at":"2026-05-17T23:41:58Z","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"},"paper":{"abstract_excerpt":"Recent works show that Graph Neural Networks (GNNs) are highly non-robust with respect to adversarial attacks on both the graph structure and the node attributes, making their outcomes unreliable. We propose the first method for certifiable (non-)robustness of graph convolutional networks with respect to perturbations of the node attributes. We consider the case of binary node attributes (e.g. bag-of-words) and perturbations that are L_0-bounded. If a node has been certified with our method, it is guaranteed to be robust under any possible perturbation given the attack model. Likewise, we can ","authors_text":"Daniel Z\\\"ugner, Stephan G\\\"unnemann","cross_cats":["cs.CR","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-28T15:40:10Z","title":"Certifiable Robustness and Robust Training for Graph Convolutional Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.12269","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":"sha256:65eac8c5fa0e7bb913016762e06849019251865d92603d10a5ed46400deb3c05","target":"record","created_at":"2026-05-17T23:41:58Z","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":"54660fb9fa77ff2ebe44374b9153aa8451ee69fd975e74568ca99f67b9193ffe","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-28T15:40:10Z","title_canon_sha256":"f2aef535bed3cccb1579cda2a3d01ce246837a6c8b4fc8f7a0187aaf9412ec6f"},"schema_version":"1.0","source":{"id":"1906.12269","kind":"arxiv","version":1}},"canonical_sha256":"ff539fdc8c8103269a1af7d13c95b5d7429ff3746c120f484f1b94090148f1c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff539fdc8c8103269a1af7d13c95b5d7429ff3746c120f484f1b94090148f1c6","first_computed_at":"2026-05-17T23:41:58.810024Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:58.810024Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8pe59G7Pfrnczq5EWlcH5CCFFm+TNWLqBQFBygqlivF9hRoEFPwLXi0k+2wp1/KMNkqdFfBOT3lHQKUAqL3pAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:58.810536Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.12269","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65eac8c5fa0e7bb913016762e06849019251865d92603d10a5ed46400deb3c05","sha256:6b54ba89c3f6e854a8d5e16ad0b0fa01763c085f09d381bee0525f9e339b5372"],"state_sha256":"95786c722c8ea359acc71d54b1acefdf49bbcabc1cfa5526df646436606ddd66"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"voB0Vr8MobVz0ToP+A9+Mfq5hdHJkAsNsoL54eZzLX35sekZrkfDN6kllsxQXlLUlEeXf0aYUQsUrf54GotJCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T15:25:33.989498Z","bundle_sha256":"d9d5ff95ce9e0c10d39e6402c0e0a9c12295cc74152c349baffb502e28e548f1"}}