{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JHGTMQ5PWX2DQXN6MMXEDWOELJ","short_pith_number":"pith:JHGTMQ5P","canonical_record":{"source":{"id":"2412.13516","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T05:33:16Z","cross_cats_sorted":[],"title_canon_sha256":"0d10d1bba7885c7af3505c6914ba02f77a4a94e903c3b5b9d4d862b94a37ed18","abstract_canon_sha256":"322a1e14bb35bc743d8917dc2ee8d9b34a24bc4809aa773096524a90fe91b058"},"schema_version":"1.0"},"canonical_sha256":"49cd3643afb5f4385dbe632e41d9c45a6a2fdaba4c775aa1fe255b696f20e114","source":{"kind":"arxiv","id":"2412.13516","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.13516","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"arxiv_version","alias_value":"2412.13516v4","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.13516","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"pith_short_12","alias_value":"JHGTMQ5PWX2D","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"pith_short_16","alias_value":"JHGTMQ5PWX2DQXN6","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"pith_short_8","alias_value":"JHGTMQ5P","created_at":"2026-07-05T10:38:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JHGTMQ5PWX2DQXN6MMXEDWOELJ","target":"record","payload":{"canonical_record":{"source":{"id":"2412.13516","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T05:33:16Z","cross_cats_sorted":[],"title_canon_sha256":"0d10d1bba7885c7af3505c6914ba02f77a4a94e903c3b5b9d4d862b94a37ed18","abstract_canon_sha256":"322a1e14bb35bc743d8917dc2ee8d9b34a24bc4809aa773096524a90fe91b058"},"schema_version":"1.0"},"canonical_sha256":"49cd3643afb5f4385dbe632e41d9c45a6a2fdaba4c775aa1fe255b696f20e114","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:38:40.318071Z","signature_b64":"8fOESzqxoaVenx7srskVtXbmRm1r6jFBZBIFVfehkYiRzJwUQ7/imiFZ7CENfCVVcEoUVMG7C0SNWBzypAs/Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"49cd3643afb5f4385dbe632e41d9c45a6a2fdaba4c775aa1fe255b696f20e114","last_reissued_at":"2026-07-05T10:38:40.317590Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:38:40.317590Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.13516","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":"2026-07-05T10:38:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/m/JlQ4bC2gWJVdP01udzOp9uQO7J6fMnUzCFOq/m9B1jnEqg+Ndhn/wjaE0yICG1zo/3iPl4+Y9Qd6TJKSiDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T12:26:01.591530Z"},"content_sha256":"625777b53aae3611cb68e9f151efd04c219a55135c06b97c03e6a66e2b774810","schema_version":"1.0","event_id":"sha256:625777b53aae3611cb68e9f151efd04c219a55135c06b97c03e6a66e2b774810"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JHGTMQ5PWX2DQXN6MMXEDWOELJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Causal Transition Matrix for Instance-dependent Label Noise","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Jiahui Li, Jun Zhou, Kun Kuang, Long Chen, Tai-Wei Chang, Ximing Li","submitted_at":"2024-12-18T05:33:16Z","abstract_excerpt":"Noisy labels are both inevitable and problematic in machine learning methods, as they negatively impact models' generalization ability by causing overfitting. In the context of learning with noise, the transition matrix plays a crucial role in the design of statistically consistent algorithms. However, the transition matrix is often considered unidentifiable. One strand of methods typically addresses this problem by assuming that the transition matrix is instance-independent; that is, the probability of mislabeling a particular instance is not influenced by its characteristics or attributes. T"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.13516","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/2412.13516/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":"2026-07-05T10:38:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hlRIScJypIlKJsdcOVWYOVstv7y5MafbrpFtw+HwxMSPajTtk5GqEv3Yeo5iVGjjJS5reI5KIEA+Pi7ttwjfCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T12:26:01.592037Z"},"content_sha256":"77e6534809969b5b5596fcc13e14fd4978c2d152b7c99b2479053efd2e591bdc","schema_version":"1.0","event_id":"sha256:77e6534809969b5b5596fcc13e14fd4978c2d152b7c99b2479053efd2e591bdc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ/bundle.json","state_url":"https://pith.science/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ/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":"2026-08-12T12:26:01Z","links":{"resolver":"https://pith.science/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ","bundle":"https://pith.science/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ/bundle.json","state":"https://pith.science/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JHGTMQ5PWX2DQXN6MMXEDWOELJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JHGTMQ5PWX2DQXN6MMXEDWOELJ","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":"322a1e14bb35bc743d8917dc2ee8d9b34a24bc4809aa773096524a90fe91b058","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T05:33:16Z","title_canon_sha256":"0d10d1bba7885c7af3505c6914ba02f77a4a94e903c3b5b9d4d862b94a37ed18"},"schema_version":"1.0","source":{"id":"2412.13516","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.13516","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"arxiv_version","alias_value":"2412.13516v4","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.13516","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"pith_short_12","alias_value":"JHGTMQ5PWX2D","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"pith_short_16","alias_value":"JHGTMQ5PWX2DQXN6","created_at":"2026-07-05T10:38:40Z"},{"alias_kind":"pith_short_8","alias_value":"JHGTMQ5P","created_at":"2026-07-05T10:38:40Z"}],"graph_snapshots":[{"event_id":"sha256:77e6534809969b5b5596fcc13e14fd4978c2d152b7c99b2479053efd2e591bdc","target":"graph","created_at":"2026-07-05T10:38:40Z","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/2412.13516/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Noisy labels are both inevitable and problematic in machine learning methods, as they negatively impact models' generalization ability by causing overfitting. In the context of learning with noise, the transition matrix plays a crucial role in the design of statistically consistent algorithms. However, the transition matrix is often considered unidentifiable. One strand of methods typically addresses this problem by assuming that the transition matrix is instance-independent; that is, the probability of mislabeling a particular instance is not influenced by its characteristics or attributes. T","authors_text":"Jiahui Li, Jun Zhou, Kun Kuang, Long Chen, Tai-Wei Chang, Ximing Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T05:33:16Z","title":"Learning Causal Transition Matrix for Instance-dependent Label Noise"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.13516","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":"sha256:625777b53aae3611cb68e9f151efd04c219a55135c06b97c03e6a66e2b774810","target":"record","created_at":"2026-07-05T10:38:40Z","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":"322a1e14bb35bc743d8917dc2ee8d9b34a24bc4809aa773096524a90fe91b058","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T05:33:16Z","title_canon_sha256":"0d10d1bba7885c7af3505c6914ba02f77a4a94e903c3b5b9d4d862b94a37ed18"},"schema_version":"1.0","source":{"id":"2412.13516","kind":"arxiv","version":4}},"canonical_sha256":"49cd3643afb5f4385dbe632e41d9c45a6a2fdaba4c775aa1fe255b696f20e114","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"49cd3643afb5f4385dbe632e41d9c45a6a2fdaba4c775aa1fe255b696f20e114","first_computed_at":"2026-07-05T10:38:40.317590Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:38:40.317590Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8fOESzqxoaVenx7srskVtXbmRm1r6jFBZBIFVfehkYiRzJwUQ7/imiFZ7CENfCVVcEoUVMG7C0SNWBzypAs/Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:38:40.318071Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.13516","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:625777b53aae3611cb68e9f151efd04c219a55135c06b97c03e6a66e2b774810","sha256:77e6534809969b5b5596fcc13e14fd4978c2d152b7c99b2479053efd2e591bdc"],"state_sha256":"53a559bba5e703d9bd5f2a907a6c7e46c06c82864eb9ce6b3340c7c6c80c8d02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AnJk/jycmGnfcoN0Y/j7Y2+SKD4Xree9PR6Ikc6ot5eO2gM5p8L3uQnOOGPWIiQ9Z7aSF8lD6Jxi2D8b2QK7BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T12:26:01.597364Z","bundle_sha256":"2e394b5d5e067000e68f9acdcb958c2a0fe326fc677b94659301ec07a5cb61db"}}