{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:XVMJMZ64K3LHZSUA6DY2DONSNI","short_pith_number":"pith:XVMJMZ64","canonical_record":{"source":{"id":"2205.03753","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T01:35:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5aa26bfe8536ecfd600e6d073e1dade3208ff5437cc1967a113544215fa704cf","abstract_canon_sha256":"249f7981fbb16422bff229c469b29b84b7c5e2ae21d782b8a0636fe2c49bd8ee"},"schema_version":"1.0"},"canonical_sha256":"bd589667dc56d67cca80f0f1a1b9b26a28e6e20df1d17f93dd7caf1acc0caeb5","source":{"kind":"arxiv","id":"2205.03753","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.03753","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2205.03753v1","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.03753","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"XVMJMZ64K3LH","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"XVMJMZ64K3LHZSUA","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"XVMJMZ64","created_at":"2026-07-05T07:17:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:XVMJMZ64K3LHZSUA6DY2DONSNI","target":"record","payload":{"canonical_record":{"source":{"id":"2205.03753","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T01:35:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5aa26bfe8536ecfd600e6d073e1dade3208ff5437cc1967a113544215fa704cf","abstract_canon_sha256":"249f7981fbb16422bff229c469b29b84b7c5e2ae21d782b8a0636fe2c49bd8ee"},"schema_version":"1.0"},"canonical_sha256":"bd589667dc56d67cca80f0f1a1b9b26a28e6e20df1d17f93dd7caf1acc0caeb5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:17:51.597091Z","signature_b64":"YMtRDk6jts/M+WueaZY/DQlMHHpxp5q7YAaMjQZXXdqXWxHkL6ljUQi/iRmRaxHpsOnCZfPDLE+nqZ1YV7XSBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd589667dc56d67cca80f0f1a1b9b26a28e6e20df1d17f93dd7caf1acc0caeb5","last_reissued_at":"2026-07-05T07:17:51.596581Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:17:51.596581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.03753","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":"2026-07-05T07:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Va3+90aPhRATxLoGkdkTcPG3TQ74Z2XYRVZXzVcMXhf6IwWUc/EpB7Z2In92EZjFB67rzbkn4QeYMruwgz9Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T19:29:58.325057Z"},"content_sha256":"83d6b056d7d461a822ce3fd467b702de087497b4eda7380e5bd2dd49407264cc","schema_version":"1.0","event_id":"sha256:83d6b056d7d461a822ce3fd467b702de087497b4eda7380e5bd2dd49407264cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:XVMJMZ64K3LHZSUA6DY2DONSNI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Bin Yan, Jian Chen, Kai Qiao, Linyuan Wang, Shuai Yang, Shuhao Shi","submitted_at":"2022-05-08T01:35:28Z","abstract_excerpt":"The Graph Convolutional Networks (GCNs) have achieved excellent results in node classification tasks, but the model's performance at low label rates is still unsatisfactory. Previous studies in Semi-Supervised Learning (SSL) for graph have focused on using network predictions to generate soft pseudo-labels or instructing message propagation, which inevitably contains the incorrect prediction due to the over-confident in the predictions. Our proposed Dual-Channel Consistency based Graph Convolutional Networks (DCC-GCN) uses dual-channel to extract embeddings from node features and topological s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.03753","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/2205.03753/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":"2026-07-05T07:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xpq5yFaJvoVnq39MgHhtiZaSKQJmoYjpqWbXr7VQ71vF0hNkDNXonjbfZw48CSrJb8buX+cRA+26Q1DwF5C5BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T19:29:58.325594Z"},"content_sha256":"d8f872f0633db70b0af6fa85b39ac8e151248a74cecbdf392efc96a9fd44e826","schema_version":"1.0","event_id":"sha256:d8f872f0633db70b0af6fa85b39ac8e151248a74cecbdf392efc96a9fd44e826"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XVMJMZ64K3LHZSUA6DY2DONSNI/bundle.json","state_url":"https://pith.science/pith/XVMJMZ64K3LHZSUA6DY2DONSNI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XVMJMZ64K3LHZSUA6DY2DONSNI/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":"2026-08-15T19:29:58Z","links":{"resolver":"https://pith.science/pith/XVMJMZ64K3LHZSUA6DY2DONSNI","bundle":"https://pith.science/pith/XVMJMZ64K3LHZSUA6DY2DONSNI/bundle.json","state":"https://pith.science/pith/XVMJMZ64K3LHZSUA6DY2DONSNI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XVMJMZ64K3LHZSUA6DY2DONSNI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:XVMJMZ64K3LHZSUA6DY2DONSNI","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":"249f7981fbb16422bff229c469b29b84b7c5e2ae21d782b8a0636fe2c49bd8ee","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T01:35:28Z","title_canon_sha256":"5aa26bfe8536ecfd600e6d073e1dade3208ff5437cc1967a113544215fa704cf"},"schema_version":"1.0","source":{"id":"2205.03753","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.03753","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2205.03753v1","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.03753","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"XVMJMZ64K3LH","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"XVMJMZ64K3LHZSUA","created_at":"2026-07-05T07:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"XVMJMZ64","created_at":"2026-07-05T07:17:51Z"}],"graph_snapshots":[{"event_id":"sha256:d8f872f0633db70b0af6fa85b39ac8e151248a74cecbdf392efc96a9fd44e826","target":"graph","created_at":"2026-07-05T07:17:51Z","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/2205.03753/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Graph Convolutional Networks (GCNs) have achieved excellent results in node classification tasks, but the model's performance at low label rates is still unsatisfactory. Previous studies in Semi-Supervised Learning (SSL) for graph have focused on using network predictions to generate soft pseudo-labels or instructing message propagation, which inevitably contains the incorrect prediction due to the over-confident in the predictions. Our proposed Dual-Channel Consistency based Graph Convolutional Networks (DCC-GCN) uses dual-channel to extract embeddings from node features and topological s","authors_text":"Bin Yan, Jian Chen, Kai Qiao, Linyuan Wang, Shuai Yang, Shuhao Shi","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T01:35:28Z","title":"Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.03753","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":"sha256:83d6b056d7d461a822ce3fd467b702de087497b4eda7380e5bd2dd49407264cc","target":"record","created_at":"2026-07-05T07:17:51Z","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":"249f7981fbb16422bff229c469b29b84b7c5e2ae21d782b8a0636fe2c49bd8ee","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T01:35:28Z","title_canon_sha256":"5aa26bfe8536ecfd600e6d073e1dade3208ff5437cc1967a113544215fa704cf"},"schema_version":"1.0","source":{"id":"2205.03753","kind":"arxiv","version":1}},"canonical_sha256":"bd589667dc56d67cca80f0f1a1b9b26a28e6e20df1d17f93dd7caf1acc0caeb5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd589667dc56d67cca80f0f1a1b9b26a28e6e20df1d17f93dd7caf1acc0caeb5","first_computed_at":"2026-07-05T07:17:51.596581Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:17:51.596581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YMtRDk6jts/M+WueaZY/DQlMHHpxp5q7YAaMjQZXXdqXWxHkL6ljUQi/iRmRaxHpsOnCZfPDLE+nqZ1YV7XSBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:17:51.597091Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.03753","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:83d6b056d7d461a822ce3fd467b702de087497b4eda7380e5bd2dd49407264cc","sha256:d8f872f0633db70b0af6fa85b39ac8e151248a74cecbdf392efc96a9fd44e826"],"state_sha256":"8fe5e387d0ca01836a7c453ce73c4294af4ac0924e05d51f2e8c6b7a75685378"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+nHdDpo/rFKfCDRkTP+3gZ4yQtE43iG+mxSWTEF7AugytODqI0xoL4WEQDUvAertEGXVyxAhYovmidarxEi7Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T19:29:58.330458Z","bundle_sha256":"0961c664701cd059fcdc512a14012de2211f73f548581fc8a7c5f4d6f3d431cf"}}