{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:NZORKEYOBDT6VLBSMTI5AFJRCV","short_pith_number":"pith:NZORKEYO","canonical_record":{"source":{"id":"2111.11638","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T03:58:56Z","cross_cats_sorted":[],"title_canon_sha256":"bb1813092f9b85f28c958660dc5f59ee8934a4ff5b557ee82d59d2795a079bc1","abstract_canon_sha256":"d7d9fb3366929bce1e52a8dd413af320b4a34c5ac298611846446db1d6a447cf"},"schema_version":"1.0"},"canonical_sha256":"6e5d15130e08e7eaac3264d1d015311556f4f18bbc4470df139b3524eea8c24c","source":{"kind":"arxiv","id":"2111.11638","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.11638","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"arxiv_version","alias_value":"2111.11638v1","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.11638","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"pith_short_12","alias_value":"NZORKEYOBDT6","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"pith_short_16","alias_value":"NZORKEYOBDT6VLBS","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"pith_short_8","alias_value":"NZORKEYO","created_at":"2026-07-05T03:34:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:NZORKEYOBDT6VLBSMTI5AFJRCV","target":"record","payload":{"canonical_record":{"source":{"id":"2111.11638","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T03:58:56Z","cross_cats_sorted":[],"title_canon_sha256":"bb1813092f9b85f28c958660dc5f59ee8934a4ff5b557ee82d59d2795a079bc1","abstract_canon_sha256":"d7d9fb3366929bce1e52a8dd413af320b4a34c5ac298611846446db1d6a447cf"},"schema_version":"1.0"},"canonical_sha256":"6e5d15130e08e7eaac3264d1d015311556f4f18bbc4470df139b3524eea8c24c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:34:11.119883Z","signature_b64":"h0qBvoe0N4lKIxjbBq93iai3uE0F1o50Q88AADaYoKLtK/ol7aF+eb3OxaEIwhkBDsBWnq4H6O1lFnu0JzlKCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e5d15130e08e7eaac3264d1d015311556f4f18bbc4470df139b3524eea8c24c","last_reissued_at":"2026-07-05T03:34:11.119522Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:34:11.119522Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.11638","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":"2026-07-05T03:34:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+IljmVeu+qzIUxdrxTv9TYkJwWORLdZD+trY20gBgAe6LK8d2omF8dq/g407l48dnGaJ+oVmkO+lqoiMkpK8Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:28:34.173666Z"},"content_sha256":"bf2dc53eb918e932fb865fd145fab9b76ea214a2f90fcd7aef46a447c75930c0","schema_version":"1.0","event_id":"sha256:bf2dc53eb918e932fb865fd145fab9b76ea214a2f90fcd7aef46a447c75930c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:NZORKEYOBDT6VLBSMTI5AFJRCV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Network In Graph Neural Network","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"David Paul Wipf, Jiahang Li, Muhan Zhang, Runjie Ma, Xiang Song","submitted_at":"2021-11-23T03:58:56Z","abstract_excerpt":"Graph Neural Networks (GNNs) have shown success in learning from graph structured data containing node/edge feature information, with application to social networks, recommendation, fraud detection and knowledge graph reasoning. In this regard, various strategies have been proposed in the past to improve the expressiveness of GNNs. For example, one straightforward option is to simply increase the parameter size by either expanding the hid-den dimension or increasing the number of GNN layers. However, wider hidden layers can easily lead to overfitting, and incrementally adding more GNN layers c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.11638","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/2111.11638/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":"2026-07-05T03:34:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e1E0RRP07hdutJi3FiFTXzQ/XuPyUEjpSFWi0AGKz6louXHWbRGZ4ag4Dn1dYT6ceAjIsy2giMUBUoNgSiGvAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:28:34.174046Z"},"content_sha256":"eefe6fe3138fb38d6403c1ad6a589b531f95de4954db202cf78bd689acb57959","schema_version":"1.0","event_id":"sha256:eefe6fe3138fb38d6403c1ad6a589b531f95de4954db202cf78bd689acb57959"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NZORKEYOBDT6VLBSMTI5AFJRCV/bundle.json","state_url":"https://pith.science/pith/NZORKEYOBDT6VLBSMTI5AFJRCV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NZORKEYOBDT6VLBSMTI5AFJRCV/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":"2026-07-08T19:28:34Z","links":{"resolver":"https://pith.science/pith/NZORKEYOBDT6VLBSMTI5AFJRCV","bundle":"https://pith.science/pith/NZORKEYOBDT6VLBSMTI5AFJRCV/bundle.json","state":"https://pith.science/pith/NZORKEYOBDT6VLBSMTI5AFJRCV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NZORKEYOBDT6VLBSMTI5AFJRCV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:NZORKEYOBDT6VLBSMTI5AFJRCV","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":"d7d9fb3366929bce1e52a8dd413af320b4a34c5ac298611846446db1d6a447cf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T03:58:56Z","title_canon_sha256":"bb1813092f9b85f28c958660dc5f59ee8934a4ff5b557ee82d59d2795a079bc1"},"schema_version":"1.0","source":{"id":"2111.11638","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.11638","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"arxiv_version","alias_value":"2111.11638v1","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.11638","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"pith_short_12","alias_value":"NZORKEYOBDT6","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"pith_short_16","alias_value":"NZORKEYOBDT6VLBS","created_at":"2026-07-05T03:34:11Z"},{"alias_kind":"pith_short_8","alias_value":"NZORKEYO","created_at":"2026-07-05T03:34:11Z"}],"graph_snapshots":[{"event_id":"sha256:eefe6fe3138fb38d6403c1ad6a589b531f95de4954db202cf78bd689acb57959","target":"graph","created_at":"2026-07-05T03:34:11Z","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/2111.11638/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) have shown success in learning from graph structured data containing node/edge feature information, with application to social networks, recommendation, fraud detection and knowledge graph reasoning. In this regard, various strategies have been proposed in the past to improve the expressiveness of GNNs. For example, one straightforward option is to simply increase the parameter size by either expanding the hid-den dimension or increasing the number of GNN layers. However, wider hidden layers can easily lead to overfitting, and incrementally adding more GNN layers c","authors_text":"David Paul Wipf, Jiahang Li, Muhan Zhang, Runjie Ma, Xiang Song","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T03:58:56Z","title":"Network In Graph Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.11638","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:bf2dc53eb918e932fb865fd145fab9b76ea214a2f90fcd7aef46a447c75930c0","target":"record","created_at":"2026-07-05T03:34:11Z","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":"d7d9fb3366929bce1e52a8dd413af320b4a34c5ac298611846446db1d6a447cf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T03:58:56Z","title_canon_sha256":"bb1813092f9b85f28c958660dc5f59ee8934a4ff5b557ee82d59d2795a079bc1"},"schema_version":"1.0","source":{"id":"2111.11638","kind":"arxiv","version":1}},"canonical_sha256":"6e5d15130e08e7eaac3264d1d015311556f4f18bbc4470df139b3524eea8c24c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e5d15130e08e7eaac3264d1d015311556f4f18bbc4470df139b3524eea8c24c","first_computed_at":"2026-07-05T03:34:11.119522Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:34:11.119522Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h0qBvoe0N4lKIxjbBq93iai3uE0F1o50Q88AADaYoKLtK/ol7aF+eb3OxaEIwhkBDsBWnq4H6O1lFnu0JzlKCg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:34:11.119883Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.11638","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bf2dc53eb918e932fb865fd145fab9b76ea214a2f90fcd7aef46a447c75930c0","sha256:eefe6fe3138fb38d6403c1ad6a589b531f95de4954db202cf78bd689acb57959"],"state_sha256":"9870722399dfdfc5acc0a5ca9d4012ea67b8322015a2c65ec3a97456c023f070"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qL/28Slm2NdvW9yJAoAP8W46NDQc8inqKKIlWEq/rHLMcDv06WH3MQzT4SCRvVolr6k92JWurx642RD/ygofBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T19:28:34.176166Z","bundle_sha256":"d6bf836693e0059eccc446fda679c4e2cb172ffdfe17ebd3b58b954390e1f606"}}