{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:GQJ2JEICYGAKE3KXDBY56GAYNE","short_pith_number":"pith:GQJ2JEIC","canonical_record":{"source":{"id":"2212.09034","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-18T08:17:32Z","cross_cats_sorted":[],"title_canon_sha256":"1e2531eb0c278108c69f5f08b8b1c1724f4ab95f798c9ef104a165a9a2d06efc","abstract_canon_sha256":"5ab366109a5ae7b426038e77eeb1432e8633ed3dca03818ea274417825b40049"},"schema_version":"1.0"},"canonical_sha256":"3413a49102c180a26d571871df1818693c6303ceb5e63c7a3a6c22480f0460ce","source":{"kind":"arxiv","id":"2212.09034","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.09034","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"arxiv_version","alias_value":"2212.09034v4","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.09034","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"pith_short_12","alias_value":"GQJ2JEICYGAK","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"pith_short_16","alias_value":"GQJ2JEICYGAKE3KX","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"pith_short_8","alias_value":"GQJ2JEIC","created_at":"2026-07-05T06:37:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:GQJ2JEICYGAKE3KXDBY56GAYNE","target":"record","payload":{"canonical_record":{"source":{"id":"2212.09034","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-18T08:17:32Z","cross_cats_sorted":[],"title_canon_sha256":"1e2531eb0c278108c69f5f08b8b1c1724f4ab95f798c9ef104a165a9a2d06efc","abstract_canon_sha256":"5ab366109a5ae7b426038e77eeb1432e8633ed3dca03818ea274417825b40049"},"schema_version":"1.0"},"canonical_sha256":"3413a49102c180a26d571871df1818693c6303ceb5e63c7a3a6c22480f0460ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:37:30.731934Z","signature_b64":"/1kVdoC/LlPfi3gN+oY5Aao6EvBcGyiy4k6+yq9zQcrTBidkbaah1Z39EfpiB1kTBc+AJeUQE8K9iCknmqqFDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3413a49102c180a26d571871df1818693c6303ceb5e63c7a3a6c22480f0460ce","last_reissued_at":"2026-07-05T06:37:30.731427Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:37:30.731427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.09034","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:37:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nGqj9R7IVE8hoS2DmI5aLb9IwS1WsQsqSCKTRH8RpZ7MTEF59hXLK98+96t8iQCA3R5yw6IVrD/qTscRwZN2DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:50:40.127639Z"},"content_sha256":"cb55ebc007fd782abded45f425b6d3f683b2debcecae4f3502438dfb931a44df","schema_version":"1.0","event_id":"sha256:cb55ebc007fd782abded45f425b6d3f683b2debcecae4f3502438dfb931a44df"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:GQJ2JEICYGAKE3KXDBY56GAYNE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chenxiao Yang, Jiahua Wang, Junchi Yan, Qitian Wu","submitted_at":"2022-12-18T08:17:32Z","abstract_excerpt":"Graph neural networks (GNNs), as the de-facto model class for representation learning on graphs, are built upon the multi-layer perceptrons (MLP) architecture with additional message passing layers to allow features to flow across nodes. While conventional wisdom commonly attributes the success of GNNs to their advanced expressivity, we conjecture that this is not the main cause of GNNs' superiority in node-level prediction tasks. This paper pinpoints the major source of GNNs' performance gain to their intrinsic generalization capability, by introducing an intermediate model class dubbed as P("},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.09034","kind":"arxiv","version":4},"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/2212.09034/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":"2026-07-05T06:37:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4gAQBLwz6PzO2jM2wWgkMURSa7AcXuVV+Y5dS+m+1oEBkClWisD+i7VHbhNenfwLmlD9+cMOjvt5UBxInw+HBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:50:40.128146Z"},"content_sha256":"48a24d001d1f62b58c1291d53c1277ca9e0b500f480b3155d42724d0191fe549","schema_version":"1.0","event_id":"sha256:48a24d001d1f62b58c1291d53c1277ca9e0b500f480b3155d42724d0191fe549"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GQJ2JEICYGAKE3KXDBY56GAYNE/bundle.json","state_url":"https://pith.science/pith/GQJ2JEICYGAKE3KXDBY56GAYNE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GQJ2JEICYGAKE3KXDBY56GAYNE/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":"2026-08-05T19:50:40Z","links":{"resolver":"https://pith.science/pith/GQJ2JEICYGAKE3KXDBY56GAYNE","bundle":"https://pith.science/pith/GQJ2JEICYGAKE3KXDBY56GAYNE/bundle.json","state":"https://pith.science/pith/GQJ2JEICYGAKE3KXDBY56GAYNE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GQJ2JEICYGAKE3KXDBY56GAYNE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:GQJ2JEICYGAKE3KXDBY56GAYNE","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":"5ab366109a5ae7b426038e77eeb1432e8633ed3dca03818ea274417825b40049","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-18T08:17:32Z","title_canon_sha256":"1e2531eb0c278108c69f5f08b8b1c1724f4ab95f798c9ef104a165a9a2d06efc"},"schema_version":"1.0","source":{"id":"2212.09034","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.09034","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"arxiv_version","alias_value":"2212.09034v4","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.09034","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"pith_short_12","alias_value":"GQJ2JEICYGAK","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"pith_short_16","alias_value":"GQJ2JEICYGAKE3KX","created_at":"2026-07-05T06:37:30Z"},{"alias_kind":"pith_short_8","alias_value":"GQJ2JEIC","created_at":"2026-07-05T06:37:30Z"}],"graph_snapshots":[{"event_id":"sha256:48a24d001d1f62b58c1291d53c1277ca9e0b500f480b3155d42724d0191fe549","target":"graph","created_at":"2026-07-05T06:37:30Z","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/2212.09034/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph neural networks (GNNs), as the de-facto model class for representation learning on graphs, are built upon the multi-layer perceptrons (MLP) architecture with additional message passing layers to allow features to flow across nodes. While conventional wisdom commonly attributes the success of GNNs to their advanced expressivity, we conjecture that this is not the main cause of GNNs' superiority in node-level prediction tasks. This paper pinpoints the major source of GNNs' performance gain to their intrinsic generalization capability, by introducing an intermediate model class dubbed as P(","authors_text":"Chenxiao Yang, Jiahua Wang, Junchi Yan, Qitian Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-18T08:17:32Z","title":"Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.09034","kind":"arxiv","version":4},"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:cb55ebc007fd782abded45f425b6d3f683b2debcecae4f3502438dfb931a44df","target":"record","created_at":"2026-07-05T06:37:30Z","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":"5ab366109a5ae7b426038e77eeb1432e8633ed3dca03818ea274417825b40049","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-18T08:17:32Z","title_canon_sha256":"1e2531eb0c278108c69f5f08b8b1c1724f4ab95f798c9ef104a165a9a2d06efc"},"schema_version":"1.0","source":{"id":"2212.09034","kind":"arxiv","version":4}},"canonical_sha256":"3413a49102c180a26d571871df1818693c6303ceb5e63c7a3a6c22480f0460ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3413a49102c180a26d571871df1818693c6303ceb5e63c7a3a6c22480f0460ce","first_computed_at":"2026-07-05T06:37:30.731427Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:37:30.731427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/1kVdoC/LlPfi3gN+oY5Aao6EvBcGyiy4k6+yq9zQcrTBidkbaah1Z39EfpiB1kTBc+AJeUQE8K9iCknmqqFDw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:37:30.731934Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.09034","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cb55ebc007fd782abded45f425b6d3f683b2debcecae4f3502438dfb931a44df","sha256:48a24d001d1f62b58c1291d53c1277ca9e0b500f480b3155d42724d0191fe549"],"state_sha256":"6a116b03e45557fb7032e3148317b91b6430802962904a7b3341b7878d38a6d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UQX36cu9QmAPQK0RjaBOB/8d1liTLc+7UD1IgtUdGqE3C3R4qlMpaK3ysAgCK1xDo+VKwU26lhP2tXSADguCBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:50:40.132034Z","bundle_sha256":"764bbd6f960b0c9cedf565190eea5bbf985a6629d739ceec82b67526b9b0d6e7"}}