{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:46F2QOJORXQ335ES7CB3Z4SZXU","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":"a9a4a83f578527fc59f32fe7de0d90e4ca06833f5a91907b249dbcd623995f73","cross_cats_sorted":["eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-09T12:54:03Z","title_canon_sha256":"955e4b218eaa241ebcfeffe068d0245dd72e90312a9e3ec6d44b26c77d39364b"},"schema_version":"1.0","source":{"id":"2206.04471","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.04471","created_at":"2026-07-05T04:30:34Z"},{"alias_kind":"arxiv_version","alias_value":"2206.04471v1","created_at":"2026-07-05T04:30:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.04471","created_at":"2026-07-05T04:30:34Z"},{"alias_kind":"pith_short_12","alias_value":"46F2QOJORXQ3","created_at":"2026-07-05T04:30:34Z"},{"alias_kind":"pith_short_16","alias_value":"46F2QOJORXQ335ES","created_at":"2026-07-05T04:30:34Z"},{"alias_kind":"pith_short_8","alias_value":"46F2QOJO","created_at":"2026-07-05T04:30:34Z"}],"graph_snapshots":[{"event_id":"sha256:484411ff871ad8e01f15ca5a1114caee1b157a317ad93e7ffedaccd3eca58e63","target":"graph","created_at":"2026-07-05T04:30:34Z","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/2206.04471/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The graph neural network (GNN) has demonstrated its superior performance in various applications. The working mechanism behind it, however, remains mysterious. GNN models are designed to learn effective representations for graph-structured data, which intrinsically coincides with the principle of graph signal denoising (GSD). Algorithm unrolling, a \"learning to optimize\" technique, has gained increasing attention due to its prospects in building efficient and interpretable neural network architectures. In this paper, we introduce a class of unrolled networks built based on truncated optimizati","authors_text":"Zepeng Zhang, Ziping Zhao","cross_cats":["eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-09T12:54:03Z","title":"Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.04471","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:f0f295561bedba74fdf7f1a721d85231d1b8dbf8f183926fef94f1f71e7a75b4","target":"record","created_at":"2026-07-05T04:30:34Z","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":"a9a4a83f578527fc59f32fe7de0d90e4ca06833f5a91907b249dbcd623995f73","cross_cats_sorted":["eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-06-09T12:54:03Z","title_canon_sha256":"955e4b218eaa241ebcfeffe068d0245dd72e90312a9e3ec6d44b26c77d39364b"},"schema_version":"1.0","source":{"id":"2206.04471","kind":"arxiv","version":1}},"canonical_sha256":"e78ba8392e8de1bdf492f883bcf259bd1d86acc88e6a9c74da549a2da6d1a000","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e78ba8392e8de1bdf492f883bcf259bd1d86acc88e6a9c74da549a2da6d1a000","first_computed_at":"2026-07-05T04:30:34.218393Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:30:34.218393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EsB9RHcrft4FBGS9N6jgjNaIRpQSwS58uJNQqcLrE9zzhJE6nHk1gKBCxZD2OHIoZw1vrwGRXFM3kYdhg3eJBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:30:34.218813Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.04471","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0f295561bedba74fdf7f1a721d85231d1b8dbf8f183926fef94f1f71e7a75b4","sha256:484411ff871ad8e01f15ca5a1114caee1b157a317ad93e7ffedaccd3eca58e63"],"state_sha256":"6da04fef9ecfbc5c42a90906c8768b3253605b8fa3f8fa2530f879ccd82a32f8"}