{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:CNWDJTWD4NIAYAWXCRCG3U65EZ","short_pith_number":"pith:CNWDJTWD","canonical_record":{"source":{"id":"2311.15502","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-27T02:59:17Z","cross_cats_sorted":[],"title_canon_sha256":"9d6ad895dcbf898e441c0dbe4ee3bf93f7239af46ba4eeedfddadca1c262db07","abstract_canon_sha256":"18bdb0dd1c7a946399e98ee6b2770c7e684cc3ae776941f332c23223db10a538"},"schema_version":"1.0"},"canonical_sha256":"136c34cec3e3500c02d714446dd3dd267cba06a7f7a7ddf578902d352c8ec2ca","source":{"kind":"arxiv","id":"2311.15502","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.15502","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"arxiv_version","alias_value":"2311.15502v4","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.15502","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"pith_short_12","alias_value":"CNWDJTWD4NIA","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"pith_short_16","alias_value":"CNWDJTWD4NIAYAWX","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"pith_short_8","alias_value":"CNWDJTWD","created_at":"2026-07-05T09:19:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:CNWDJTWD4NIAYAWXCRCG3U65EZ","target":"record","payload":{"canonical_record":{"source":{"id":"2311.15502","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-27T02:59:17Z","cross_cats_sorted":[],"title_canon_sha256":"9d6ad895dcbf898e441c0dbe4ee3bf93f7239af46ba4eeedfddadca1c262db07","abstract_canon_sha256":"18bdb0dd1c7a946399e98ee6b2770c7e684cc3ae776941f332c23223db10a538"},"schema_version":"1.0"},"canonical_sha256":"136c34cec3e3500c02d714446dd3dd267cba06a7f7a7ddf578902d352c8ec2ca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:19:06.776198Z","signature_b64":"+kochq7tURSZEgSVI/JYtyqM4YMyhvNRR78V/8iHfabYf6jJ7pWfP5huurW4qrBewZ/AJrik+SEe03Iqew7PCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"136c34cec3e3500c02d714446dd3dd267cba06a7f7a7ddf578902d352c8ec2ca","last_reissued_at":"2026-07-05T09:19:06.775610Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:19:06.775610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.15502","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:19:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HhCe4EgocEzFF+I3l2HKPAeqplyE7UISPIxZPqJUVmKXh5+W3VXN82ULOboQL23keXgWD8nyYFjG1HTkcIaGAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:55:58.150846Z"},"content_sha256":"9d0b27415a9473d2d08a022505dd6236eeb79be1851aa4571f561a1cfbefbec4","schema_version":"1.0","event_id":"sha256:9d0b27415a9473d2d08a022505dd6236eeb79be1851aa4571f561a1cfbefbec4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:CNWDJTWD4NIAYAWXCRCG3U65EZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Gang Niu, Masashi Sugiyama, Takashi Ishida, Wei Wang, Yu-Jie Zhang","submitted_at":"2023-11-27T02:59:17Z","abstract_excerpt":"Complementary-label learning is a weakly supervised learning problem in which each training example is associated with one or multiple complementary labels indicating the classes to which it does not belong. Existing consistent approaches have relied on the uniform distribution assumption to model the generation of complementary labels, or on an ordinary-label training set to estimate the transition matrix in non-uniform cases. However, either condition may not be satisfied in real-world scenarios. In this paper, we propose a novel consistent approach that does not rely on these conditions. In"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.15502","kind":"arxiv","version":4},"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/2311.15502/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":"2026-07-05T09:19:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g5KUfD+yimK7Ho/xnj/H9i/ELb3W9R8CPV8fhzCT6VzZWKbkRF+6tVZDP4BOGyETq+r5Shi3YEi00dXQ9LXzBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:55:58.151219Z"},"content_sha256":"640d645fcc85882d927cc108c3dab0257188a4fde550846d79e1cbb239831ce7","schema_version":"1.0","event_id":"sha256:640d645fcc85882d927cc108c3dab0257188a4fde550846d79e1cbb239831ce7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ/bundle.json","state_url":"https://pith.science/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ/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":"2026-07-07T11:55:58Z","links":{"resolver":"https://pith.science/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ","bundle":"https://pith.science/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ/bundle.json","state":"https://pith.science/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CNWDJTWD4NIAYAWXCRCG3U65EZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CNWDJTWD4NIAYAWXCRCG3U65EZ","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":"18bdb0dd1c7a946399e98ee6b2770c7e684cc3ae776941f332c23223db10a538","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-27T02:59:17Z","title_canon_sha256":"9d6ad895dcbf898e441c0dbe4ee3bf93f7239af46ba4eeedfddadca1c262db07"},"schema_version":"1.0","source":{"id":"2311.15502","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.15502","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"arxiv_version","alias_value":"2311.15502v4","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.15502","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"pith_short_12","alias_value":"CNWDJTWD4NIA","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"pith_short_16","alias_value":"CNWDJTWD4NIAYAWX","created_at":"2026-07-05T09:19:06Z"},{"alias_kind":"pith_short_8","alias_value":"CNWDJTWD","created_at":"2026-07-05T09:19:06Z"}],"graph_snapshots":[{"event_id":"sha256:640d645fcc85882d927cc108c3dab0257188a4fde550846d79e1cbb239831ce7","target":"graph","created_at":"2026-07-05T09:19:06Z","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/2311.15502/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Complementary-label learning is a weakly supervised learning problem in which each training example is associated with one or multiple complementary labels indicating the classes to which it does not belong. Existing consistent approaches have relied on the uniform distribution assumption to model the generation of complementary labels, or on an ordinary-label training set to estimate the transition matrix in non-uniform cases. However, either condition may not be satisfied in real-world scenarios. In this paper, we propose a novel consistent approach that does not rely on these conditions. In","authors_text":"Gang Niu, Masashi Sugiyama, Takashi Ishida, Wei Wang, Yu-Jie Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-27T02:59:17Z","title":"Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.15502","kind":"arxiv","version":4},"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":"sha256:9d0b27415a9473d2d08a022505dd6236eeb79be1851aa4571f561a1cfbefbec4","target":"record","created_at":"2026-07-05T09:19:06Z","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":"18bdb0dd1c7a946399e98ee6b2770c7e684cc3ae776941f332c23223db10a538","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-27T02:59:17Z","title_canon_sha256":"9d6ad895dcbf898e441c0dbe4ee3bf93f7239af46ba4eeedfddadca1c262db07"},"schema_version":"1.0","source":{"id":"2311.15502","kind":"arxiv","version":4}},"canonical_sha256":"136c34cec3e3500c02d714446dd3dd267cba06a7f7a7ddf578902d352c8ec2ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"136c34cec3e3500c02d714446dd3dd267cba06a7f7a7ddf578902d352c8ec2ca","first_computed_at":"2026-07-05T09:19:06.775610Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:19:06.775610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+kochq7tURSZEgSVI/JYtyqM4YMyhvNRR78V/8iHfabYf6jJ7pWfP5huurW4qrBewZ/AJrik+SEe03Iqew7PCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:19:06.776198Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.15502","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9d0b27415a9473d2d08a022505dd6236eeb79be1851aa4571f561a1cfbefbec4","sha256:640d645fcc85882d927cc108c3dab0257188a4fde550846d79e1cbb239831ce7"],"state_sha256":"e1508284b6bf5c52044ee85728abd2643167505711a112a65787ced23deb93f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hQ8LBbiWqyBIDLFyUZUHp0LWGtVOLH9wHyYiog5TuHF/N7DkqEg/NoA13PW1ToEdnYLhPuwm21cWFwGvWJZABQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T11:55:58.153156Z","bundle_sha256":"20d5d47c1c849e834051d76cdf063534c904fccf2059fe3fd3983c3e5aa30991"}}