{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MMS5MDNDYYGZKLAAHCHFF4SR3N","short_pith_number":"pith:MMS5MDND","canonical_record":{"source":{"id":"2403.14715","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-19T06:46:24Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"517009cc3d09174f406d815e9f934e2ab90aabc7e009a8b8f584e5ffce073d0b","abstract_canon_sha256":"f5bc382737d6040a91fa8fbd2be972fc04d5d7ccad3b7e544867c797500859b0"},"schema_version":"1.0"},"canonical_sha256":"6325d60da3c60d952c00388e52f251db78fa48a3a4f53eca0616fabc3016966d","source":{"kind":"arxiv","id":"2403.14715","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.14715","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"arxiv_version","alias_value":"2403.14715v3","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14715","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"pith_short_12","alias_value":"MMS5MDNDYYGZ","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"pith_short_16","alias_value":"MMS5MDNDYYGZKLAA","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"pith_short_8","alias_value":"MMS5MDND","created_at":"2026-07-05T10:17:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MMS5MDNDYYGZKLAAHCHFF4SR3N","target":"record","payload":{"canonical_record":{"source":{"id":"2403.14715","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-19T06:46:24Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"517009cc3d09174f406d815e9f934e2ab90aabc7e009a8b8f584e5ffce073d0b","abstract_canon_sha256":"f5bc382737d6040a91fa8fbd2be972fc04d5d7ccad3b7e544867c797500859b0"},"schema_version":"1.0"},"canonical_sha256":"6325d60da3c60d952c00388e52f251db78fa48a3a4f53eca0616fabc3016966d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:17:07.259583Z","signature_b64":"L4Ry6yVT50Si71Pvvo+CJ+NqiK8shKAxMfnrav+mxF5QovwNlfRms28k1DLC1mowhXr2y+NUfy+jUlOfacePDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6325d60da3c60d952c00388e52f251db78fa48a3a4f53eca0616fabc3016966d","last_reissued_at":"2026-07-05T10:17:07.259118Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:17:07.259118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.14715","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":"2026-07-05T10:17:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EU7SLZwsdyvSj/H7+4/+J1IOH8+z/KSbwWnJ2lfRREdPkdx2fBBIam+xK0EaAcryfUTWEwroi5EMkXzM5K1IAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T23:42:42.575926Z"},"content_sha256":"30e236a6fa47ae4b5633d64df380f54eadd2f42fddb6c597cb0b7002bd1d17a9","schema_version":"1.0","event_id":"sha256:30e236a6fa47ae4b5633d64df380f54eadd2f42fddb6c597cb0b7002bd1d17a9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MMS5MDNDYYGZKLAAHCHFF4SR3N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Christos-Savvas Bouganis, Gianni Franchi, Guoxuan Xia, Olivier Laurent","submitted_at":"2024-03-19T06:46:24Z","abstract_excerpt":"Label smoothing (LS) is a popular regularisation method for training neural networks as it is effective in improving test accuracy and is simple to implement. ``Hard'' one-hot labels are ``smoothed'' by uniformly distributing probability mass to other classes, reducing overfitting. Prior work has suggested that in some cases LS can degrade selective classification (SC) -- where the aim is to reject misclassifications using a model's uncertainty. In this work, we first demonstrate empirically across an extended range of large-scale tasks and architectures that LS consistently degrades SC. We th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14715","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/2403.14715/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":"2026-07-05T10:17:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C4j2b1BdyLNcGqt1MFAmJzpYtJwBVajd5nkCm8TS2YWO1GozwEFjvwNiQMGaj7US61LcuTNf1ZL+5YZHIzoVAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T23:42:42.576220Z"},"content_sha256":"bbdfa3f93333a84ab8d8abab5af4a01e0688bcafb7ea1e3da9b2637ea1525462","schema_version":"1.0","event_id":"sha256:bbdfa3f93333a84ab8d8abab5af4a01e0688bcafb7ea1e3da9b2637ea1525462"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N/bundle.json","state_url":"https://pith.science/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N/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":"2026-08-13T23:42:42Z","links":{"resolver":"https://pith.science/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N","bundle":"https://pith.science/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N/bundle.json","state":"https://pith.science/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MMS5MDNDYYGZKLAAHCHFF4SR3N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MMS5MDNDYYGZKLAAHCHFF4SR3N","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":"f5bc382737d6040a91fa8fbd2be972fc04d5d7ccad3b7e544867c797500859b0","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-19T06:46:24Z","title_canon_sha256":"517009cc3d09174f406d815e9f934e2ab90aabc7e009a8b8f584e5ffce073d0b"},"schema_version":"1.0","source":{"id":"2403.14715","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.14715","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"arxiv_version","alias_value":"2403.14715v3","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14715","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"pith_short_12","alias_value":"MMS5MDNDYYGZ","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"pith_short_16","alias_value":"MMS5MDNDYYGZKLAA","created_at":"2026-07-05T10:17:07Z"},{"alias_kind":"pith_short_8","alias_value":"MMS5MDND","created_at":"2026-07-05T10:17:07Z"}],"graph_snapshots":[{"event_id":"sha256:bbdfa3f93333a84ab8d8abab5af4a01e0688bcafb7ea1e3da9b2637ea1525462","target":"graph","created_at":"2026-07-05T10:17:07Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2403.14715/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Label smoothing (LS) is a popular regularisation method for training neural networks as it is effective in improving test accuracy and is simple to implement. ``Hard'' one-hot labels are ``smoothed'' by uniformly distributing probability mass to other classes, reducing overfitting. Prior work has suggested that in some cases LS can degrade selective classification (SC) -- where the aim is to reject misclassifications using a model's uncertainty. In this work, we first demonstrate empirically across an extended range of large-scale tasks and architectures that LS consistently degrades SC. We th","authors_text":"Christos-Savvas Bouganis, Gianni Franchi, Guoxuan Xia, Olivier Laurent","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-19T06:46:24Z","title":"Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14715","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":"sha256:30e236a6fa47ae4b5633d64df380f54eadd2f42fddb6c597cb0b7002bd1d17a9","target":"record","created_at":"2026-07-05T10:17:07Z","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":"f5bc382737d6040a91fa8fbd2be972fc04d5d7ccad3b7e544867c797500859b0","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-03-19T06:46:24Z","title_canon_sha256":"517009cc3d09174f406d815e9f934e2ab90aabc7e009a8b8f584e5ffce073d0b"},"schema_version":"1.0","source":{"id":"2403.14715","kind":"arxiv","version":3}},"canonical_sha256":"6325d60da3c60d952c00388e52f251db78fa48a3a4f53eca0616fabc3016966d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6325d60da3c60d952c00388e52f251db78fa48a3a4f53eca0616fabc3016966d","first_computed_at":"2026-07-05T10:17:07.259118Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:17:07.259118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L4Ry6yVT50Si71Pvvo+CJ+NqiK8shKAxMfnrav+mxF5QovwNlfRms28k1DLC1mowhXr2y+NUfy+jUlOfacePDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:17:07.259583Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.14715","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:30e236a6fa47ae4b5633d64df380f54eadd2f42fddb6c597cb0b7002bd1d17a9","sha256:bbdfa3f93333a84ab8d8abab5af4a01e0688bcafb7ea1e3da9b2637ea1525462"],"state_sha256":"4568b63e7c53f8e73443df4245047b526c66f9fd2e2dc010b29f942d2b24d811"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TSR3dZtb6Ty1dHvjx+Ay+0hIkusEUh72Mcd/Ica8dH0RZ8kNw4HEWxS+3F2Xy4XntaizjCPl3v32REj7+/DVCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T23:42:42.597896Z","bundle_sha256":"8392961667cd1eabc36447441e652e8ccf456c4e4417cf2a328394aa0fa733e6"}}