{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:LC7HLERVBXDRIG4QYVXVW3KJXM","short_pith_number":"pith:LC7HLERV","canonical_record":{"source":{"id":"2212.04055","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-08T03:35:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6273f47106f254e1614b12b995aab0ef1e6f7dc27664f40580a2f4702210deae","abstract_canon_sha256":"a13cd11d22902e5f6495b1c91da5ec0612829adf6c3876ad6abc8e8d907c6099"},"schema_version":"1.0"},"canonical_sha256":"58be7592350dc7141b90c56f5b6d49bb1835e36da833f3482c18bae337c3984a","source":{"kind":"arxiv","id":"2212.04055","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.04055","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"arxiv_version","alias_value":"2212.04055v3","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.04055","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"pith_short_12","alias_value":"LC7HLERVBXDR","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"pith_short_16","alias_value":"LC7HLERVBXDRIG4Q","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"pith_short_8","alias_value":"LC7HLERV","created_at":"2026-07-05T06:19:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:LC7HLERVBXDRIG4QYVXVW3KJXM","target":"record","payload":{"canonical_record":{"source":{"id":"2212.04055","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-08T03:35:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6273f47106f254e1614b12b995aab0ef1e6f7dc27664f40580a2f4702210deae","abstract_canon_sha256":"a13cd11d22902e5f6495b1c91da5ec0612829adf6c3876ad6abc8e8d907c6099"},"schema_version":"1.0"},"canonical_sha256":"58be7592350dc7141b90c56f5b6d49bb1835e36da833f3482c18bae337c3984a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:19:54.399185Z","signature_b64":"MjZ0E5uqIb7RTmtaskSoEmedbpl6KeqiLL/8gJPkzkqPKipzNXNSN/YhyDG7dgpM9RMR3xjjgVnWoZs22/eXCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"58be7592350dc7141b90c56f5b6d49bb1835e36da833f3482c18bae337c3984a","last_reissued_at":"2026-07-05T06:19:54.398696Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:19:54.398696Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.04055","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":"2026-07-05T06:19:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y0qSdUz00RX0PMbrOtuYhyPpGUqF4QCEyXf/KylK2GL8mNk9GRQlzxKIt+qo09o3dICrXXOXDkpp1KWH8gjmDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T11:53:26.167109Z"},"content_sha256":"d0463e1752ce0c0536c101a089650215de6fa1e1caf60b211eac17b2c721ef72","schema_version":"1.0","event_id":"sha256:d0463e1752ce0c0536c101a089650215de6fa1e1caf60b211eac17b2c721ef72"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:LC7HLERVBXDRIG4QYVXVW3KJXM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mitigating Memorization of Noisy Labels by Clipping the Model Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Bo An, Gang Niu, Hongxin Wei, Huiping Zhuang, Lei Feng, Renchunzi Xie, Yixuan Li","submitted_at":"2022-12-08T03:35:42Z","abstract_excerpt":"In the presence of noisy labels, designing robust loss functions is critical for securing the generalization performance of deep neural networks. Cross Entropy (CE) loss has been shown to be not robust to noisy labels due to its unboundedness. To alleviate this issue, existing works typically design specialized robust losses with the symmetric condition, which usually lead to the underfitting issue. In this paper, our key idea is to induce a loss bound at the logit level, thus universally enhancing the noise robustness of existing losses. Specifically, we propose logit clipping (LogitClip), wh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.04055","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/2212.04055/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":"2026-07-05T06:19:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s6H4IBcYNT75HLDAKvEewLahYYdnuyExqPuUBXpbwZ7WTroWsi8IQXDcvHsuy0oDE7sCEMhvpsxguLmVlT+3AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T11:53:26.167614Z"},"content_sha256":"2714bcbca7a86ccf18853dc5981d40de7b0f759a5a5f3a5966476230b494a4b8","schema_version":"1.0","event_id":"sha256:2714bcbca7a86ccf18853dc5981d40de7b0f759a5a5f3a5966476230b494a4b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LC7HLERVBXDRIG4QYVXVW3KJXM/bundle.json","state_url":"https://pith.science/pith/LC7HLERVBXDRIG4QYVXVW3KJXM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LC7HLERVBXDRIG4QYVXVW3KJXM/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":"2026-08-23T11:53:26Z","links":{"resolver":"https://pith.science/pith/LC7HLERVBXDRIG4QYVXVW3KJXM","bundle":"https://pith.science/pith/LC7HLERVBXDRIG4QYVXVW3KJXM/bundle.json","state":"https://pith.science/pith/LC7HLERVBXDRIG4QYVXVW3KJXM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LC7HLERVBXDRIG4QYVXVW3KJXM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LC7HLERVBXDRIG4QYVXVW3KJXM","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":"a13cd11d22902e5f6495b1c91da5ec0612829adf6c3876ad6abc8e8d907c6099","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-08T03:35:42Z","title_canon_sha256":"6273f47106f254e1614b12b995aab0ef1e6f7dc27664f40580a2f4702210deae"},"schema_version":"1.0","source":{"id":"2212.04055","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.04055","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"arxiv_version","alias_value":"2212.04055v3","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.04055","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"pith_short_12","alias_value":"LC7HLERVBXDR","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"pith_short_16","alias_value":"LC7HLERVBXDRIG4Q","created_at":"2026-07-05T06:19:54Z"},{"alias_kind":"pith_short_8","alias_value":"LC7HLERV","created_at":"2026-07-05T06:19:54Z"}],"graph_snapshots":[{"event_id":"sha256:2714bcbca7a86ccf18853dc5981d40de7b0f759a5a5f3a5966476230b494a4b8","target":"graph","created_at":"2026-07-05T06:19:54Z","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/2212.04055/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the presence of noisy labels, designing robust loss functions is critical for securing the generalization performance of deep neural networks. Cross Entropy (CE) loss has been shown to be not robust to noisy labels due to its unboundedness. To alleviate this issue, existing works typically design specialized robust losses with the symmetric condition, which usually lead to the underfitting issue. In this paper, our key idea is to induce a loss bound at the logit level, thus universally enhancing the noise robustness of existing losses. Specifically, we propose logit clipping (LogitClip), wh","authors_text":"Bo An, Gang Niu, Hongxin Wei, Huiping Zhuang, Lei Feng, Renchunzi Xie, Yixuan Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-08T03:35:42Z","title":"Mitigating Memorization of Noisy Labels by Clipping the Model Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.04055","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:d0463e1752ce0c0536c101a089650215de6fa1e1caf60b211eac17b2c721ef72","target":"record","created_at":"2026-07-05T06:19:54Z","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":"a13cd11d22902e5f6495b1c91da5ec0612829adf6c3876ad6abc8e8d907c6099","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-08T03:35:42Z","title_canon_sha256":"6273f47106f254e1614b12b995aab0ef1e6f7dc27664f40580a2f4702210deae"},"schema_version":"1.0","source":{"id":"2212.04055","kind":"arxiv","version":3}},"canonical_sha256":"58be7592350dc7141b90c56f5b6d49bb1835e36da833f3482c18bae337c3984a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"58be7592350dc7141b90c56f5b6d49bb1835e36da833f3482c18bae337c3984a","first_computed_at":"2026-07-05T06:19:54.398696Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:19:54.398696Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MjZ0E5uqIb7RTmtaskSoEmedbpl6KeqiLL/8gJPkzkqPKipzNXNSN/YhyDG7dgpM9RMR3xjjgVnWoZs22/eXCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:19:54.399185Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.04055","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0463e1752ce0c0536c101a089650215de6fa1e1caf60b211eac17b2c721ef72","sha256:2714bcbca7a86ccf18853dc5981d40de7b0f759a5a5f3a5966476230b494a4b8"],"state_sha256":"5443b2f8464c55057fc154075de7387ed83e45b992cfa0743f41d6401673e0fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9TyJ8gh6jrktS2aXhVpcDFfhfYjIsRV5WKPLZZSYboUHBqWBbFZNxYm6fRftQpONf9zpLiTiiHc9rdlbHRxnCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T11:53:26.171600Z","bundle_sha256":"daba8fa86adbb28630128132bdfde07e5f00d315ce01c051c2d07b88fa4e73ad"}}