{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:W3POGGSX7WRJOTJNWB3TRT5Z6Y","short_pith_number":"pith:W3POGGSX","canonical_record":{"source":{"id":"1902.07429","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-20T07:19:05Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"aeebf4b16808d5bbf930534182284344e7700fef9e8f7fb2953a2be5db80f3ef","abstract_canon_sha256":"c2323ea9541ff39f21e234520895e03218d3b1f6cdb34541d142a412c0b93ed1"},"schema_version":"1.0"},"canonical_sha256":"b6dee31a57fda2974d2db07738cfb9f62c0676dea9d1568589571ee154e9a9b6","source":{"kind":"arxiv","id":"1902.07429","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.07429","created_at":"2026-05-17T23:53:07Z"},{"alias_kind":"arxiv_version","alias_value":"1902.07429v1","created_at":"2026-05-17T23:53:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.07429","created_at":"2026-05-17T23:53:07Z"},{"alias_kind":"pith_short_12","alias_value":"W3POGGSX7WRJ","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"W3POGGSX7WRJOTJN","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"W3POGGSX","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:W3POGGSX7WRJOTJNWB3TRT5Z6Y","target":"record","payload":{"canonical_record":{"source":{"id":"1902.07429","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-20T07:19:05Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"aeebf4b16808d5bbf930534182284344e7700fef9e8f7fb2953a2be5db80f3ef","abstract_canon_sha256":"c2323ea9541ff39f21e234520895e03218d3b1f6cdb34541d142a412c0b93ed1"},"schema_version":"1.0"},"canonical_sha256":"b6dee31a57fda2974d2db07738cfb9f62c0676dea9d1568589571ee154e9a9b6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:53:07.927673Z","signature_b64":"X1FhqTtVwA44Nwg9PeIVJATWQfqyKLA8NiiJz2OrD1MabBrgjq7JN7F0zhFeAvAw8WwDNoUWu9+DDjpDr1FYDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6dee31a57fda2974d2db07738cfb9f62c0676dea9d1568589571ee154e9a9b6","last_reissued_at":"2026-05-17T23:53:07.927054Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:53:07.927054Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.07429","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":"2026-05-17T23:53:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HDKisr9MYBUmP13paBBWzGl2/eSxPTxOxlHvRgFjLamD0Etnh9r7e0HTrnGiyhTXX9WTF/nB3UYLTDmJDDtCBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T15:29:18.541326Z"},"content_sha256":"246f02467a5e3a62a3ae43cf34b820936ed58e52f65eb0161ee4b00e00190fbd","schema_version":"1.0","event_id":"sha256:246f02467a5e3a62a3ae43cf34b820936ed58e52f65eb0161ee4b00e00190fbd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:W3POGGSX7WRJOTJNWB3TRT5Z6Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning with Inadequate and Incorrect Supervision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Chen Gong, Dacheng Tao, Hengmin Zhang, Jian Yang","submitted_at":"2019-02-20T07:19:05Z","abstract_excerpt":"Practically, we are often in the dilemma that the labeled data at hand are inadequate to train a reliable classifier, and more seriously, some of these labeled data may be mistakenly labeled due to the various human factors. Therefore, this paper proposes a novel semi-supervised learning paradigm that can handle both label insufficiency and label inaccuracy. To address label insufficiency, we use a graph to bridge the data points so that the label information can be propagated from the scarce labeled examples to unlabeled examples along the graph edges. To address label inaccuracy, Graph Trend"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.07429","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":""},"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":"2026-05-17T23:53:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GQT1Mhmjj39IA0oDcOBozgS8X8zxhHngn9x3E3H9HB+3FUVBIopQm2aaSFTPfqB8fVyEdBw395ICy7IPL6kKBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T15:29:18.541679Z"},"content_sha256":"391ab2c35cb3111533e52c441f77d750f8e71877ddd0715e52f5c4090ae5be70","schema_version":"1.0","event_id":"sha256:391ab2c35cb3111533e52c441f77d750f8e71877ddd0715e52f5c4090ae5be70"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y/bundle.json","state_url":"https://pith.science/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y/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":"2026-06-01T15:29:18Z","links":{"resolver":"https://pith.science/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y","bundle":"https://pith.science/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y/bundle.json","state":"https://pith.science/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W3POGGSX7WRJOTJNWB3TRT5Z6Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:W3POGGSX7WRJOTJNWB3TRT5Z6Y","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":"c2323ea9541ff39f21e234520895e03218d3b1f6cdb34541d142a412c0b93ed1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-20T07:19:05Z","title_canon_sha256":"aeebf4b16808d5bbf930534182284344e7700fef9e8f7fb2953a2be5db80f3ef"},"schema_version":"1.0","source":{"id":"1902.07429","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.07429","created_at":"2026-05-17T23:53:07Z"},{"alias_kind":"arxiv_version","alias_value":"1902.07429v1","created_at":"2026-05-17T23:53:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.07429","created_at":"2026-05-17T23:53:07Z"},{"alias_kind":"pith_short_12","alias_value":"W3POGGSX7WRJ","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"W3POGGSX7WRJOTJN","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"W3POGGSX","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:391ab2c35cb3111533e52c441f77d750f8e71877ddd0715e52f5c4090ae5be70","target":"graph","created_at":"2026-05-17T23:53:07Z","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"},"paper":{"abstract_excerpt":"Practically, we are often in the dilemma that the labeled data at hand are inadequate to train a reliable classifier, and more seriously, some of these labeled data may be mistakenly labeled due to the various human factors. Therefore, this paper proposes a novel semi-supervised learning paradigm that can handle both label insufficiency and label inaccuracy. To address label insufficiency, we use a graph to bridge the data points so that the label information can be propagated from the scarce labeled examples to unlabeled examples along the graph edges. To address label inaccuracy, Graph Trend","authors_text":"Chen Gong, Dacheng Tao, Hengmin Zhang, Jian Yang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-20T07:19:05Z","title":"Learning with Inadequate and Incorrect Supervision"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.07429","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":"sha256:246f02467a5e3a62a3ae43cf34b820936ed58e52f65eb0161ee4b00e00190fbd","target":"record","created_at":"2026-05-17T23:53:07Z","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":"c2323ea9541ff39f21e234520895e03218d3b1f6cdb34541d142a412c0b93ed1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-20T07:19:05Z","title_canon_sha256":"aeebf4b16808d5bbf930534182284344e7700fef9e8f7fb2953a2be5db80f3ef"},"schema_version":"1.0","source":{"id":"1902.07429","kind":"arxiv","version":1}},"canonical_sha256":"b6dee31a57fda2974d2db07738cfb9f62c0676dea9d1568589571ee154e9a9b6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6dee31a57fda2974d2db07738cfb9f62c0676dea9d1568589571ee154e9a9b6","first_computed_at":"2026-05-17T23:53:07.927054Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:07.927054Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X1FhqTtVwA44Nwg9PeIVJATWQfqyKLA8NiiJz2OrD1MabBrgjq7JN7F0zhFeAvAw8WwDNoUWu9+DDjpDr1FYDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:07.927673Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.07429","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:246f02467a5e3a62a3ae43cf34b820936ed58e52f65eb0161ee4b00e00190fbd","sha256:391ab2c35cb3111533e52c441f77d750f8e71877ddd0715e52f5c4090ae5be70"],"state_sha256":"26b0ac82c39e4ce1009ffac4bcfe192ca699579501b5f6bbe2759183518964cc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pq5FhgT2VA63HjY5WMSzHFcJ6CjBi8d1aURqLcQ2HvqP3qqHQgVWRbkXDAnFTvi7qtVpwnS1VvjjEbZEgFdEDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T15:29:18.543660Z","bundle_sha256":"1469e5c50f71474468c043bad802a38f3c3819ab41d6835f9b9e0715c0d45752"}}