{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:ZK2DH27NYA7PADE4QA6UXP22DJ","short_pith_number":"pith:ZK2DH27N","canonical_record":{"source":{"id":"2211.06605","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-12T08:03:57Z","cross_cats_sorted":[],"title_canon_sha256":"af61b811ba39f9ef2b2fde362e04acb24dfa5e319fe2bf705b5f311205eb5cb9","abstract_canon_sha256":"ce67a817c6dc28eaad4fa3d28d46833799ec8b096e5f6c4ebc111c27e0254737"},"schema_version":"1.0"},"canonical_sha256":"cab433ebedc03ef00c9c803d4bbf5a1a53284c4266083ca64f563bc2532eccc3","source":{"kind":"arxiv","id":"2211.06605","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.06605","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.06605v2","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06605","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"pith_short_12","alias_value":"ZK2DH27NYA7P","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"pith_short_16","alias_value":"ZK2DH27NYA7PADE4","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"pith_short_8","alias_value":"ZK2DH27N","created_at":"2026-07-05T05:47:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:ZK2DH27NYA7PADE4QA6UXP22DJ","target":"record","payload":{"canonical_record":{"source":{"id":"2211.06605","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-12T08:03:57Z","cross_cats_sorted":[],"title_canon_sha256":"af61b811ba39f9ef2b2fde362e04acb24dfa5e319fe2bf705b5f311205eb5cb9","abstract_canon_sha256":"ce67a817c6dc28eaad4fa3d28d46833799ec8b096e5f6c4ebc111c27e0254737"},"schema_version":"1.0"},"canonical_sha256":"cab433ebedc03ef00c9c803d4bbf5a1a53284c4266083ca64f563bc2532eccc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:47:04.803916Z","signature_b64":"ZwqC61PDPlR5j5sk880l+w9fjUGghayn550ElnaW89NysFvFkZ2VdV2NOypI+wqhn7mxBhHJvkKY2LntAnQ7CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cab433ebedc03ef00c9c803d4bbf5a1a53284c4266083ca64f563bc2532eccc3","last_reissued_at":"2026-07-05T05:47:04.803478Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:47:04.803478Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.06605","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":"2026-07-05T05:47:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Se1FpbdBZH7RgIOc4RDoHd9dd+GCfj8Dxec+C9PtklXBzOUb1FwOHv8D1wGkRWnKU30Cm2gZomxw+EzR9DIpBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T13:56:06.986103Z"},"content_sha256":"3792d41beac2f4ad1861e008978da12d10357bd846051784e41da63e02c95ab1","schema_version":"1.0","event_id":"sha256:3792d41beac2f4ad1861e008978da12d10357bd846051784e41da63e02c95ab1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:ZK2DH27NYA7PADE4QA6UXP22DJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Comprehensive Analysis of Over-smoothing in Graph Neural Networks from Markov Chains Perspective","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chenguang Wang, Congying Han, Tiande Guo, Weichen Zhao","submitted_at":"2022-11-12T08:03:57Z","abstract_excerpt":"The over-smoothing problem is an obstacle of developing deep graph neural network (GNN). Although many approaches to improve the over-smoothing problem have been proposed, there is still a lack of comprehensive understanding and conclusion of this problem. In this work, we analyze the over-smoothing problem from the Markov chain perspective. We focus on message passing of GNN and first establish a connection between GNNs and Markov chains on the graph. GNNs are divided into two classes of operator-consistent and operator-inconsistent based on whether the corresponding Markov chains are time-ho"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06605","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/2211.06605/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":"2026-07-05T05:47:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WJ2AXP8c2riIr1ORsTYIX1j+eZUSHg1dPAamNbNwaGQ1TBIvQFoWRm7I6bxuTHFi3oXaYK6WiWbOaWfUBHLmBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T13:56:06.986503Z"},"content_sha256":"9ebc374530fcd45880176050f5d9819b8290ebca09e9026bc1598f9b135985ea","schema_version":"1.0","event_id":"sha256:9ebc374530fcd45880176050f5d9819b8290ebca09e9026bc1598f9b135985ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZK2DH27NYA7PADE4QA6UXP22DJ/bundle.json","state_url":"https://pith.science/pith/ZK2DH27NYA7PADE4QA6UXP22DJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZK2DH27NYA7PADE4QA6UXP22DJ/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":"2026-07-20T13:56:06Z","links":{"resolver":"https://pith.science/pith/ZK2DH27NYA7PADE4QA6UXP22DJ","bundle":"https://pith.science/pith/ZK2DH27NYA7PADE4QA6UXP22DJ/bundle.json","state":"https://pith.science/pith/ZK2DH27NYA7PADE4QA6UXP22DJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZK2DH27NYA7PADE4QA6UXP22DJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ZK2DH27NYA7PADE4QA6UXP22DJ","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":"ce67a817c6dc28eaad4fa3d28d46833799ec8b096e5f6c4ebc111c27e0254737","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-12T08:03:57Z","title_canon_sha256":"af61b811ba39f9ef2b2fde362e04acb24dfa5e319fe2bf705b5f311205eb5cb9"},"schema_version":"1.0","source":{"id":"2211.06605","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.06605","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.06605v2","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06605","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"pith_short_12","alias_value":"ZK2DH27NYA7P","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"pith_short_16","alias_value":"ZK2DH27NYA7PADE4","created_at":"2026-07-05T05:47:04Z"},{"alias_kind":"pith_short_8","alias_value":"ZK2DH27N","created_at":"2026-07-05T05:47:04Z"}],"graph_snapshots":[{"event_id":"sha256:9ebc374530fcd45880176050f5d9819b8290ebca09e9026bc1598f9b135985ea","target":"graph","created_at":"2026-07-05T05:47:04Z","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/2211.06605/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The over-smoothing problem is an obstacle of developing deep graph neural network (GNN). Although many approaches to improve the over-smoothing problem have been proposed, there is still a lack of comprehensive understanding and conclusion of this problem. In this work, we analyze the over-smoothing problem from the Markov chain perspective. We focus on message passing of GNN and first establish a connection between GNNs and Markov chains on the graph. GNNs are divided into two classes of operator-consistent and operator-inconsistent based on whether the corresponding Markov chains are time-ho","authors_text":"Chenguang Wang, Congying Han, Tiande Guo, Weichen Zhao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-12T08:03:57Z","title":"Comprehensive Analysis of Over-smoothing in Graph Neural Networks from Markov Chains Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06605","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":"sha256:3792d41beac2f4ad1861e008978da12d10357bd846051784e41da63e02c95ab1","target":"record","created_at":"2026-07-05T05:47:04Z","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":"ce67a817c6dc28eaad4fa3d28d46833799ec8b096e5f6c4ebc111c27e0254737","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-12T08:03:57Z","title_canon_sha256":"af61b811ba39f9ef2b2fde362e04acb24dfa5e319fe2bf705b5f311205eb5cb9"},"schema_version":"1.0","source":{"id":"2211.06605","kind":"arxiv","version":2}},"canonical_sha256":"cab433ebedc03ef00c9c803d4bbf5a1a53284c4266083ca64f563bc2532eccc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cab433ebedc03ef00c9c803d4bbf5a1a53284c4266083ca64f563bc2532eccc3","first_computed_at":"2026-07-05T05:47:04.803478Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:47:04.803478Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZwqC61PDPlR5j5sk880l+w9fjUGghayn550ElnaW89NysFvFkZ2VdV2NOypI+wqhn7mxBhHJvkKY2LntAnQ7CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:47:04.803916Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.06605","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3792d41beac2f4ad1861e008978da12d10357bd846051784e41da63e02c95ab1","sha256:9ebc374530fcd45880176050f5d9819b8290ebca09e9026bc1598f9b135985ea"],"state_sha256":"91e0711527a83c883a8fa197221d2ee84e7cc6680416014394601e622f77e445"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W0EmhFtwOmCnhdNyrxcGi728rGqlY0FzC0wVAm4d7803SKs/VZgEzBidN+hVGMM+hu8XN9DJPexIvEpPzlIiBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-20T13:56:06.989274Z","bundle_sha256":"9f491318592529e483417f942a296d1e1f24422c21921bd20220cb1f289924af"}}