{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KWBY6D6WMN44NHJP3QWOXTQ4VB","short_pith_number":"pith:KWBY6D6W","canonical_record":{"source":{"id":"2406.10017","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-14T13:27:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5b09f67ff19d941b77fba95d395a86b055db5d963ff5e1e18ff3052cf168b6f1","abstract_canon_sha256":"4721dfa9faa0ded4731ce1f77accb8b95d2e0a420d09533de2fa870601cfaec6"},"schema_version":"1.0"},"canonical_sha256":"55838f0fd66379c69d2fdc2cebce1ca878cf838a94f5b663985436c6a6d3f3f3","source":{"kind":"arxiv","id":"2406.10017","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.10017","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"arxiv_version","alias_value":"2406.10017v1","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.10017","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"pith_short_12","alias_value":"KWBY6D6WMN44","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"pith_short_16","alias_value":"KWBY6D6WMN44NHJP","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"pith_short_8","alias_value":"KWBY6D6W","created_at":"2026-07-05T08:32:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KWBY6D6WMN44NHJP3QWOXTQ4VB","target":"record","payload":{"canonical_record":{"source":{"id":"2406.10017","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-14T13:27:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5b09f67ff19d941b77fba95d395a86b055db5d963ff5e1e18ff3052cf168b6f1","abstract_canon_sha256":"4721dfa9faa0ded4731ce1f77accb8b95d2e0a420d09533de2fa870601cfaec6"},"schema_version":"1.0"},"canonical_sha256":"55838f0fd66379c69d2fdc2cebce1ca878cf838a94f5b663985436c6a6d3f3f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:03.286628Z","signature_b64":"UR0j07Zkouh1yA/JuSkk1Sg+tTV+VI4vCYfZrbq3pQ6A6vWWqOmizbptlW9IbbHBktoa3rib3mCIn6mWSDXiCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55838f0fd66379c69d2fdc2cebce1ca878cf838a94f5b663985436c6a6d3f3f3","last_reissued_at":"2026-07-05T08:32:03.285842Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:03.285842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.10017","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BKO6sFnNPDJwXgzlVjFt2KXf/OTubOkyGowYRtUZlfYwBK1E2nHzBwXJ1mp/IkhQKKKFfAwTebuf6ug5tmpECg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T21:33:44.570065Z"},"content_sha256":"ab77edbb034af2da5abc11d4b745275982a5c5c678beaa8cb0d74ab16b88793d","schema_version":"1.0","event_id":"sha256:ab77edbb034af2da5abc11d4b745275982a5c5c678beaa8cb0d74ab16b88793d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KWBY6D6WMN44NHJP3QWOXTQ4VB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chan-Hyun Youn, Gyusang Cho","submitted_at":"2024-06-14T13:27:56Z","abstract_excerpt":"After the revelation that neural networks tend to produce overconfident predictions, the problem of calibration, which aims to align confidence with accuracy to enhance the reliability of predictions, has gained significant importance. Several solutions based on calibration maps have been proposed to address the problem of recalibrating a trained classifier using additional datasets. In this paper, we offer an algorithm that transforms the weights of the last layer of the classifier, distinct from the calibration-map-based approach. We concentrate on the geometry of the final linear layer, spe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.10017","kind":"arxiv","version":1},"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/2406.10017/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":"2026-07-05T08:32:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mqy18e3+FDtFPcV+2ogJqPlRISmP0uAlYapkZrurmOW5HssXS3WgvyxzabY6dRfAPXPz10/e54isPnoLF6p+AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T21:33:44.570562Z"},"content_sha256":"8c2cdcf7dd7778d6d8a94f360460e059278246280134ca345c659044144a2843","schema_version":"1.0","event_id":"sha256:8c2cdcf7dd7778d6d8a94f360460e059278246280134ca345c659044144a2843"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB/bundle.json","state_url":"https://pith.science/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB/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":"2026-08-03T21:33:44Z","links":{"resolver":"https://pith.science/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB","bundle":"https://pith.science/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB/bundle.json","state":"https://pith.science/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KWBY6D6WMN44NHJP3QWOXTQ4VB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KWBY6D6WMN44NHJP3QWOXTQ4VB","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":"4721dfa9faa0ded4731ce1f77accb8b95d2e0a420d09533de2fa870601cfaec6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-14T13:27:56Z","title_canon_sha256":"5b09f67ff19d941b77fba95d395a86b055db5d963ff5e1e18ff3052cf168b6f1"},"schema_version":"1.0","source":{"id":"2406.10017","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.10017","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"arxiv_version","alias_value":"2406.10017v1","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.10017","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"pith_short_12","alias_value":"KWBY6D6WMN44","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"pith_short_16","alias_value":"KWBY6D6WMN44NHJP","created_at":"2026-07-05T08:32:03Z"},{"alias_kind":"pith_short_8","alias_value":"KWBY6D6W","created_at":"2026-07-05T08:32:03Z"}],"graph_snapshots":[{"event_id":"sha256:8c2cdcf7dd7778d6d8a94f360460e059278246280134ca345c659044144a2843","target":"graph","created_at":"2026-07-05T08:32:03Z","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/2406.10017/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"After the revelation that neural networks tend to produce overconfident predictions, the problem of calibration, which aims to align confidence with accuracy to enhance the reliability of predictions, has gained significant importance. Several solutions based on calibration maps have been proposed to address the problem of recalibrating a trained classifier using additional datasets. In this paper, we offer an algorithm that transforms the weights of the last layer of the classifier, distinct from the calibration-map-based approach. We concentrate on the geometry of the final linear layer, spe","authors_text":"Chan-Hyun Youn, Gyusang Cho","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-14T13:27:56Z","title":"Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.10017","kind":"arxiv","version":1},"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:ab77edbb034af2da5abc11d4b745275982a5c5c678beaa8cb0d74ab16b88793d","target":"record","created_at":"2026-07-05T08:32:03Z","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":"4721dfa9faa0ded4731ce1f77accb8b95d2e0a420d09533de2fa870601cfaec6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-14T13:27:56Z","title_canon_sha256":"5b09f67ff19d941b77fba95d395a86b055db5d963ff5e1e18ff3052cf168b6f1"},"schema_version":"1.0","source":{"id":"2406.10017","kind":"arxiv","version":1}},"canonical_sha256":"55838f0fd66379c69d2fdc2cebce1ca878cf838a94f5b663985436c6a6d3f3f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"55838f0fd66379c69d2fdc2cebce1ca878cf838a94f5b663985436c6a6d3f3f3","first_computed_at":"2026-07-05T08:32:03.285842Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:03.285842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UR0j07Zkouh1yA/JuSkk1Sg+tTV+VI4vCYfZrbq3pQ6A6vWWqOmizbptlW9IbbHBktoa3rib3mCIn6mWSDXiCw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:03.286628Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.10017","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab77edbb034af2da5abc11d4b745275982a5c5c678beaa8cb0d74ab16b88793d","sha256:8c2cdcf7dd7778d6d8a94f360460e059278246280134ca345c659044144a2843"],"state_sha256":"591518c34612658dd30c6ca13b6965f60caf81c65665b184b57605f318ba96ad"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nv7OJQwOfj63DlhjUztAuJapYEyzechFNJN4kjvZdl1P8JqtB0C9RzwBUYyKaEH88hSX/jJmnm10bfpe3iCvAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T21:33:44.573790Z","bundle_sha256":"278869e74ac4d0b9297fefef9655b2ce5dccbdd0e54e84500e9ac1a66ba9c09e"}}