{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TI6VQVWDQZKFWX5EM5OQKPGA37","short_pith_number":"pith:TI6VQVWD","canonical_record":{"source":{"id":"2410.13373","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T09:23:53Z","cross_cats_sorted":[],"title_canon_sha256":"e2fcdb52c1dbe86cf6afd844af9825b4153538135b19ad7c2505a37a587a2116","abstract_canon_sha256":"2bde7be47793d54fece6556c4bfd6427f1d82eccd794050db8df45b888f3eb27"},"schema_version":"1.0"},"canonical_sha256":"9a3d5856c386545b5fa4675d053cc0dfce2e612f893bce918d8a9c18ee2632c7","source":{"kind":"arxiv","id":"2410.13373","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.13373","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"arxiv_version","alias_value":"2410.13373v2","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.13373","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"pith_short_12","alias_value":"TI6VQVWDQZKF","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"pith_short_16","alias_value":"TI6VQVWDQZKFWX5E","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"pith_short_8","alias_value":"TI6VQVWD","created_at":"2026-07-05T10:47:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TI6VQVWDQZKFWX5EM5OQKPGA37","target":"record","payload":{"canonical_record":{"source":{"id":"2410.13373","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T09:23:53Z","cross_cats_sorted":[],"title_canon_sha256":"e2fcdb52c1dbe86cf6afd844af9825b4153538135b19ad7c2505a37a587a2116","abstract_canon_sha256":"2bde7be47793d54fece6556c4bfd6427f1d82eccd794050db8df45b888f3eb27"},"schema_version":"1.0"},"canonical_sha256":"9a3d5856c386545b5fa4675d053cc0dfce2e612f893bce918d8a9c18ee2632c7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:47:31.914714Z","signature_b64":"DV5vY/c70oT/p1PwIUUWPP9XcxEkeC2gVJyF0DAoe1zRUYT29WbwIwvelkzQDg5p/0fdYQUe1K1KMAtqcjWHAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9a3d5856c386545b5fa4675d053cc0dfce2e612f893bce918d8a9c18ee2632c7","last_reissued_at":"2026-07-05T10:47:31.914264Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:47:31.914264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.13373","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":"2026-07-05T10:47:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h9AvnaDfN2BBpPmOeF1UH+jKoO5CQ5NaqjZ+Wcr5hoSYjTfRTuX42HrTnRcQhf7ifYmDUx9kr/7iS+V4gBi4Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:59:32.364118Z"},"content_sha256":"6eb76d28817f0cfaabf4c5a1d46d85c9351c6a78b9a6f296026c308cec8012bf","schema_version":"1.0","event_id":"sha256:6eb76d28817f0cfaabf4c5a1d46d85c9351c6a78b9a6f296026c308cec8012bf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TI6VQVWDQZKFWX5EM5OQKPGA37","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Kangkang Lu, Meiyu Liang, Tat-Seng Chua, Xiao Wang, Yanhua Yu, Yimeng Ren, Yuling Wang, Yunshan Ma, Zhiyong Huang","submitted_at":"2024-10-17T09:23:53Z","abstract_excerpt":"Graph neural networks (GNNs) have demonstrated excellent performance in semi-supervised node classification tasks. Despite this, two primary challenges persist: heterogeneity and heterophily. Each of these two challenges can significantly hinder the performance of GNNs. Heterogeneity refers to a graph with multiple types of nodes or edges, while heterophily refers to the fact that connected nodes are more likely to have dissimilar attributes or labels. Although there have been few works studying heterogeneous heterophilic graphs, they either only consider the heterophily of specific meta-paths"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.13373","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/2410.13373/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":"2026-07-05T10:47:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ESbB5y1TjLWl1MHs6h0wkPbxJ1g75/KiVV3011OybTKNv18Yos3xqK1xi5xjTfxxW2UJx72+Zht3WzVjfWJmDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:59:32.364643Z"},"content_sha256":"da7fedceea080b4cfdf05b74581c28e052007aacf0f6ae3fdd57c614197988c4","schema_version":"1.0","event_id":"sha256:da7fedceea080b4cfdf05b74581c28e052007aacf0f6ae3fdd57c614197988c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TI6VQVWDQZKFWX5EM5OQKPGA37/bundle.json","state_url":"https://pith.science/pith/TI6VQVWDQZKFWX5EM5OQKPGA37/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TI6VQVWDQZKFWX5EM5OQKPGA37/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":"2026-08-19T17:59:32Z","links":{"resolver":"https://pith.science/pith/TI6VQVWDQZKFWX5EM5OQKPGA37","bundle":"https://pith.science/pith/TI6VQVWDQZKFWX5EM5OQKPGA37/bundle.json","state":"https://pith.science/pith/TI6VQVWDQZKFWX5EM5OQKPGA37/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TI6VQVWDQZKFWX5EM5OQKPGA37/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TI6VQVWDQZKFWX5EM5OQKPGA37","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":"2bde7be47793d54fece6556c4bfd6427f1d82eccd794050db8df45b888f3eb27","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T09:23:53Z","title_canon_sha256":"e2fcdb52c1dbe86cf6afd844af9825b4153538135b19ad7c2505a37a587a2116"},"schema_version":"1.0","source":{"id":"2410.13373","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.13373","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"arxiv_version","alias_value":"2410.13373v2","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.13373","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"pith_short_12","alias_value":"TI6VQVWDQZKF","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"pith_short_16","alias_value":"TI6VQVWDQZKFWX5E","created_at":"2026-07-05T10:47:31Z"},{"alias_kind":"pith_short_8","alias_value":"TI6VQVWD","created_at":"2026-07-05T10:47:31Z"}],"graph_snapshots":[{"event_id":"sha256:da7fedceea080b4cfdf05b74581c28e052007aacf0f6ae3fdd57c614197988c4","target":"graph","created_at":"2026-07-05T10:47:31Z","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/2410.13373/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph neural networks (GNNs) have demonstrated excellent performance in semi-supervised node classification tasks. Despite this, two primary challenges persist: heterogeneity and heterophily. Each of these two challenges can significantly hinder the performance of GNNs. Heterogeneity refers to a graph with multiple types of nodes or edges, while heterophily refers to the fact that connected nodes are more likely to have dissimilar attributes or labels. Although there have been few works studying heterogeneous heterophilic graphs, they either only consider the heterophily of specific meta-paths","authors_text":"Kangkang Lu, Meiyu Liang, Tat-Seng Chua, Xiao Wang, Yanhua Yu, Yimeng Ren, Yuling Wang, Yunshan Ma, Zhiyong Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T09:23:53Z","title":"Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.13373","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":"sha256:6eb76d28817f0cfaabf4c5a1d46d85c9351c6a78b9a6f296026c308cec8012bf","target":"record","created_at":"2026-07-05T10:47:31Z","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":"2bde7be47793d54fece6556c4bfd6427f1d82eccd794050db8df45b888f3eb27","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-10-17T09:23:53Z","title_canon_sha256":"e2fcdb52c1dbe86cf6afd844af9825b4153538135b19ad7c2505a37a587a2116"},"schema_version":"1.0","source":{"id":"2410.13373","kind":"arxiv","version":2}},"canonical_sha256":"9a3d5856c386545b5fa4675d053cc0dfce2e612f893bce918d8a9c18ee2632c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a3d5856c386545b5fa4675d053cc0dfce2e612f893bce918d8a9c18ee2632c7","first_computed_at":"2026-07-05T10:47:31.914264Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:47:31.914264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DV5vY/c70oT/p1PwIUUWPP9XcxEkeC2gVJyF0DAoe1zRUYT29WbwIwvelkzQDg5p/0fdYQUe1K1KMAtqcjWHAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:47:31.914714Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.13373","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6eb76d28817f0cfaabf4c5a1d46d85c9351c6a78b9a6f296026c308cec8012bf","sha256:da7fedceea080b4cfdf05b74581c28e052007aacf0f6ae3fdd57c614197988c4"],"state_sha256":"e78613f366addfdfc6b80a887e6965e7e9ebc5261a3e783885e322566c88d4b2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g4bx2Vw9iwRFnIZ8tu9ueqzaLKa+RZ3JMqAyY2JRgEUX+5+JA3ILOLtTt91N3jn/wZjeQwl1+bqjVIstKoWbBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T17:59:32.370644Z","bundle_sha256":"27c34f46a3a319d51bcd511333cb817fd9f5cd9c1c1d81d890061f479d75e1fe"}}