{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GH4XN5W3OSQVDQIJYB2SNHEM7T","short_pith_number":"pith:GH4XN5W3","canonical_record":{"source":{"id":"2406.04068","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:33:45Z","cross_cats_sorted":["math.ST","stat.ML","stat.TH"],"title_canon_sha256":"d251654d1273c53c5c5e9994fdffecf76fa5c59714048c3fe64eb2b3129f75d8","abstract_canon_sha256":"144d6a427472a7b1d1f1c7aa33a8e4bc1fefa745ccd907ec62f5ac4888d59a76"},"schema_version":"1.0"},"canonical_sha256":"31f976f6db74a151c109c075269c8cfcdb0f55f66f01f3fe55a5317df66dd3b9","source":{"kind":"arxiv","id":"2406.04068","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04068","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04068v2","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04068","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"pith_short_12","alias_value":"GH4XN5W3OSQV","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"pith_short_16","alias_value":"GH4XN5W3OSQVDQIJ","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"pith_short_8","alias_value":"GH4XN5W3","created_at":"2026-07-05T10:18:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GH4XN5W3OSQVDQIJYB2SNHEM7T","target":"record","payload":{"canonical_record":{"source":{"id":"2406.04068","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:33:45Z","cross_cats_sorted":["math.ST","stat.ML","stat.TH"],"title_canon_sha256":"d251654d1273c53c5c5e9994fdffecf76fa5c59714048c3fe64eb2b3129f75d8","abstract_canon_sha256":"144d6a427472a7b1d1f1c7aa33a8e4bc1fefa745ccd907ec62f5ac4888d59a76"},"schema_version":"1.0"},"canonical_sha256":"31f976f6db74a151c109c075269c8cfcdb0f55f66f01f3fe55a5317df66dd3b9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:18:37.891086Z","signature_b64":"bun34/DoDk5mPEV5rdzyE9F6/ZRLcDTX6NMgcuBaPgHkgGCVLyiILiziS4KEMM8oKnHL//GYVTNzcsnkjlonDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"31f976f6db74a151c109c075269c8cfcdb0f55f66f01f3fe55a5317df66dd3b9","last_reissued_at":"2026-07-05T10:18:37.890588Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:18:37.890588Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.04068","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:18:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tK1DdFwo+WElC7JnKCqXYdsvqqxbLXOxwG587EpfyrpKmx71wmGdvH/MsOz6SCRJgON2bnUCZtum//jnWINFBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T13:25:33.292313Z"},"content_sha256":"45f193143d90820bf420886cb71e0e3a7a7bb2ea05ea4a41e42b4e190820210b","schema_version":"1.0","event_id":"sha256:45f193143d90820bf420886cb71e0e3a7a7bb2ea05ea4a41e42b4e190820210b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GH4XN5W3OSQVDQIJYB2SNHEM7T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reassessing How to Compare and Improve the Calibration of Machine Learning Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.ST","stat.ML","stat.TH"],"primary_cat":"cs.LG","authors_text":"Muthu Chidambaram, Rong Ge","submitted_at":"2024-06-06T13:33:45Z","abstract_excerpt":"A machine learning model is calibrated if its predicted probability for an outcome matches the observed frequency for that outcome conditional on the model prediction. This property has become increasingly important as the impact of machine learning models has continued to spread to various domains. As a result, there are now a dizzying number of recent papers on measuring and improving the calibration of (specifically deep learning) models. In this work, we reassess the reporting of calibration metrics in the recent literature. We show that there exist trivial recalibration approaches that ca"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04068","kind":"arxiv","version":2},"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/2406.04068/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":"2026-07-05T10:18:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B+dQ6nbU7x/8eIlzIX5vy+X37lMkbgQ2TBhsJh8j8rEZPLCEsI/IdDqOPqQfA7L7NDEW46YGARo23N/hO5O4AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T13:25:33.292833Z"},"content_sha256":"f2bceaa6c64e867d7a6a5a29ed361d3c6f82140b12ffb77058aa78b82a062f39","schema_version":"1.0","event_id":"sha256:f2bceaa6c64e867d7a6a5a29ed361d3c6f82140b12ffb77058aa78b82a062f39"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T/bundle.json","state_url":"https://pith.science/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T/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":"2026-08-10T13:25:33Z","links":{"resolver":"https://pith.science/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T","bundle":"https://pith.science/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T/bundle.json","state":"https://pith.science/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GH4XN5W3OSQVDQIJYB2SNHEM7T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GH4XN5W3OSQVDQIJYB2SNHEM7T","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":"144d6a427472a7b1d1f1c7aa33a8e4bc1fefa745ccd907ec62f5ac4888d59a76","cross_cats_sorted":["math.ST","stat.ML","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:33:45Z","title_canon_sha256":"d251654d1273c53c5c5e9994fdffecf76fa5c59714048c3fe64eb2b3129f75d8"},"schema_version":"1.0","source":{"id":"2406.04068","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04068","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04068v2","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04068","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"pith_short_12","alias_value":"GH4XN5W3OSQV","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"pith_short_16","alias_value":"GH4XN5W3OSQVDQIJ","created_at":"2026-07-05T10:18:37Z"},{"alias_kind":"pith_short_8","alias_value":"GH4XN5W3","created_at":"2026-07-05T10:18:37Z"}],"graph_snapshots":[{"event_id":"sha256:f2bceaa6c64e867d7a6a5a29ed361d3c6f82140b12ffb77058aa78b82a062f39","target":"graph","created_at":"2026-07-05T10:18:37Z","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/2406.04068/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A machine learning model is calibrated if its predicted probability for an outcome matches the observed frequency for that outcome conditional on the model prediction. This property has become increasingly important as the impact of machine learning models has continued to spread to various domains. As a result, there are now a dizzying number of recent papers on measuring and improving the calibration of (specifically deep learning) models. In this work, we reassess the reporting of calibration metrics in the recent literature. We show that there exist trivial recalibration approaches that ca","authors_text":"Muthu Chidambaram, Rong Ge","cross_cats":["math.ST","stat.ML","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:33:45Z","title":"Reassessing How to Compare and Improve the Calibration of Machine Learning Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04068","kind":"arxiv","version":2},"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":"sha256:45f193143d90820bf420886cb71e0e3a7a7bb2ea05ea4a41e42b4e190820210b","target":"record","created_at":"2026-07-05T10:18:37Z","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":"144d6a427472a7b1d1f1c7aa33a8e4bc1fefa745ccd907ec62f5ac4888d59a76","cross_cats_sorted":["math.ST","stat.ML","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:33:45Z","title_canon_sha256":"d251654d1273c53c5c5e9994fdffecf76fa5c59714048c3fe64eb2b3129f75d8"},"schema_version":"1.0","source":{"id":"2406.04068","kind":"arxiv","version":2}},"canonical_sha256":"31f976f6db74a151c109c075269c8cfcdb0f55f66f01f3fe55a5317df66dd3b9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"31f976f6db74a151c109c075269c8cfcdb0f55f66f01f3fe55a5317df66dd3b9","first_computed_at":"2026-07-05T10:18:37.890588Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:18:37.890588Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bun34/DoDk5mPEV5rdzyE9F6/ZRLcDTX6NMgcuBaPgHkgGCVLyiILiziS4KEMM8oKnHL//GYVTNzcsnkjlonDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:18:37.891086Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.04068","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:45f193143d90820bf420886cb71e0e3a7a7bb2ea05ea4a41e42b4e190820210b","sha256:f2bceaa6c64e867d7a6a5a29ed361d3c6f82140b12ffb77058aa78b82a062f39"],"state_sha256":"7e1e4b1d5a61dd8e935498abc6cd8c4f1e51e13143172dd5bbd03cb3f3ec371b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FNmKWs54lr5GeEc8S4xUORg+nboimYWcw41c+TsoC6s2Vh+mPcF+g61/z81472eNGD+cueU+NdZdiFVewrvKDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T13:25:33.300058Z","bundle_sha256":"52f359aaafe3a172ba2ede83bc3c43548aaaa3c808d96d92cadcd9a354de79e8"}}