{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:2ERH6GXT3A4FL2EWFK3O7DHAZF","short_pith_number":"pith:2ERH6GXT","canonical_record":{"source":{"id":"2112.01174","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-02T12:43:41Z","cross_cats_sorted":[],"title_canon_sha256":"7cda8d781037b84da51c176df2707e5c0ccb559523c662c01ce56e2c2697a046","abstract_canon_sha256":"34bb70aeb93f6be2c668cded482815b677ebc680be3c25d6930a048d168f0854"},"schema_version":"1.0"},"canonical_sha256":"d1227f1af3d83855e8962ab6ef8ce0c9532fd18bf1a29ff1a802c1efd3b39f15","source":{"kind":"arxiv","id":"2112.01174","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.01174","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"arxiv_version","alias_value":"2112.01174v3","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.01174","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"pith_short_12","alias_value":"2ERH6GXT3A4F","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"2ERH6GXT3A4FL2EW","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"2ERH6GXT","created_at":"2026-07-05T04:30:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:2ERH6GXT3A4FL2EWFK3O7DHAZF","target":"record","payload":{"canonical_record":{"source":{"id":"2112.01174","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-02T12:43:41Z","cross_cats_sorted":[],"title_canon_sha256":"7cda8d781037b84da51c176df2707e5c0ccb559523c662c01ce56e2c2697a046","abstract_canon_sha256":"34bb70aeb93f6be2c668cded482815b677ebc680be3c25d6930a048d168f0854"},"schema_version":"1.0"},"canonical_sha256":"d1227f1af3d83855e8962ab6ef8ce0c9532fd18bf1a29ff1a802c1efd3b39f15","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:30:39.804009Z","signature_b64":"mOZhE+67aNO5l1BiqAB4hbH5EkVGRdZhyzNLfGiFn726RVdY70DjwuqsvQlWqt0Y+nvxgt6rhDx/APFNXXWpDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d1227f1af3d83855e8962ab6ef8ce0c9532fd18bf1a29ff1a802c1efd3b39f15","last_reissued_at":"2026-07-05T04:30:39.803591Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:30:39.803591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2112.01174","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:30:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oqn6wMrTw1Q0IoUk1aUZBYcOswXpiCxmtqzxXPQVC5m7AJdQ1gwy/OSjwWhG1eJXXs3aijvAdRdT6D2T+dw3Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T16:00:06.465064Z"},"content_sha256":"02fe9d2afa0f1f7688d533b68835e683eb75a1554eeaca2b5905ca485508a681","schema_version":"1.0","event_id":"sha256:02fe9d2afa0f1f7688d533b68835e683eb75a1554eeaca2b5905ca485508a681"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:2ERH6GXT3A4FL2EWFK3O7DHAZF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-task Self-distillation for Graph-based Semi-Supervised Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Junzhong Ji, Lingfeng Niu, Minglong Lei, Yating Ren","submitted_at":"2021-12-02T12:43:41Z","abstract_excerpt":"Graph convolutional networks have made great progress in graph-based semi-supervised learning. Existing methods mainly assume that nodes connected by graph edges are prone to have similar attributes and labels, so that the features smoothed by local graph structures can reveal the class similarities. However, there often exist mismatches between graph structures and labels in many real-world scenarios, where the structures may propagate misleading features or labels that eventually affect the model performance. In this paper, we propose a multi-task self-distillation framework that injects sel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.01174","kind":"arxiv","version":3},"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/2112.01174/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":"2026-07-05T04:30:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CxemkInec6s3u1SOWjU1nTlvx0MAsG0GHgxOMbTnWw5AQUQH5Y9+RKCOygCW797U7E4erpMwRCto2TvmobCNDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T16:00:06.465772Z"},"content_sha256":"fb5f0ef5ce13de6838441a25cd58abe9a769406e352f6ac02c4831583e9bd980","schema_version":"1.0","event_id":"sha256:fb5f0ef5ce13de6838441a25cd58abe9a769406e352f6ac02c4831583e9bd980"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF/bundle.json","state_url":"https://pith.science/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF/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":"2026-08-17T16:00:06Z","links":{"resolver":"https://pith.science/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF","bundle":"https://pith.science/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF/bundle.json","state":"https://pith.science/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2ERH6GXT3A4FL2EWFK3O7DHAZF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:2ERH6GXT3A4FL2EWFK3O7DHAZF","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":"34bb70aeb93f6be2c668cded482815b677ebc680be3c25d6930a048d168f0854","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-02T12:43:41Z","title_canon_sha256":"7cda8d781037b84da51c176df2707e5c0ccb559523c662c01ce56e2c2697a046"},"schema_version":"1.0","source":{"id":"2112.01174","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2112.01174","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"arxiv_version","alias_value":"2112.01174v3","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.01174","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"pith_short_12","alias_value":"2ERH6GXT3A4F","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"2ERH6GXT3A4FL2EW","created_at":"2026-07-05T04:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"2ERH6GXT","created_at":"2026-07-05T04:30:39Z"}],"graph_snapshots":[{"event_id":"sha256:fb5f0ef5ce13de6838441a25cd58abe9a769406e352f6ac02c4831583e9bd980","target":"graph","created_at":"2026-07-05T04:30:39Z","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/2112.01174/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph convolutional networks have made great progress in graph-based semi-supervised learning. Existing methods mainly assume that nodes connected by graph edges are prone to have similar attributes and labels, so that the features smoothed by local graph structures can reveal the class similarities. However, there often exist mismatches between graph structures and labels in many real-world scenarios, where the structures may propagate misleading features or labels that eventually affect the model performance. In this paper, we propose a multi-task self-distillation framework that injects sel","authors_text":"Junzhong Ji, Lingfeng Niu, Minglong Lei, Yating Ren","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-02T12:43:41Z","title":"Multi-task Self-distillation for Graph-based Semi-Supervised Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.01174","kind":"arxiv","version":3},"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":"sha256:02fe9d2afa0f1f7688d533b68835e683eb75a1554eeaca2b5905ca485508a681","target":"record","created_at":"2026-07-05T04:30:39Z","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":"34bb70aeb93f6be2c668cded482815b677ebc680be3c25d6930a048d168f0854","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-12-02T12:43:41Z","title_canon_sha256":"7cda8d781037b84da51c176df2707e5c0ccb559523c662c01ce56e2c2697a046"},"schema_version":"1.0","source":{"id":"2112.01174","kind":"arxiv","version":3}},"canonical_sha256":"d1227f1af3d83855e8962ab6ef8ce0c9532fd18bf1a29ff1a802c1efd3b39f15","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d1227f1af3d83855e8962ab6ef8ce0c9532fd18bf1a29ff1a802c1efd3b39f15","first_computed_at":"2026-07-05T04:30:39.803591Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:30:39.803591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mOZhE+67aNO5l1BiqAB4hbH5EkVGRdZhyzNLfGiFn726RVdY70DjwuqsvQlWqt0Y+nvxgt6rhDx/APFNXXWpDg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:30:39.804009Z","signed_message":"canonical_sha256_bytes"},"source_id":"2112.01174","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:02fe9d2afa0f1f7688d533b68835e683eb75a1554eeaca2b5905ca485508a681","sha256:fb5f0ef5ce13de6838441a25cd58abe9a769406e352f6ac02c4831583e9bd980"],"state_sha256":"63e131722777b8ad9f6ed8dd2b2f89bbbbd05a7b4cb5fe6c7f15dced85299a02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qwr2Qru6+Xx1dcqbuAs0tf3/Av/0dl/Y+VBEEdn/VRaibRZGS/nGY+yvgH/NUX14Wwwoe9yTl0BoZrSyXw8MCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T16:00:06.474038Z","bundle_sha256":"4e7f969fdbe125c11dbc9f66fb63f08d242cbac77982ed8e9c1149579641ce38"}}