{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:A26MHF77SMH4HH22QAN6LHUQIP","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":"2e761a321280c3b5295ec5b316e3f4e1bd2a2053b059fbb44a7fd597eccf60e2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T05:57:17Z","title_canon_sha256":"70990b8d43ce1e00f7c432adbd93b6af62cf97c6e8d9d7ea12db925c636ce6f7"},"schema_version":"1.0","source":{"id":"2509.02592","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.02592","created_at":"2026-07-05T12:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"2509.02592v1","created_at":"2026-07-05T12:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02592","created_at":"2026-07-05T12:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"A26MHF77SMH4","created_at":"2026-07-05T12:03:53Z"},{"alias_kind":"pith_short_16","alias_value":"A26MHF77SMH4HH22","created_at":"2026-07-05T12:03:53Z"},{"alias_kind":"pith_short_8","alias_value":"A26MHF77","created_at":"2026-07-05T12:03:53Z"}],"graph_snapshots":[{"event_id":"sha256:ffea110b4f10589be5f4ea74a01af98ab211f3d105dd7fcd076db482a119724a","target":"graph","created_at":"2026-07-05T12:03:53Z","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/2509.02592/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Class imbalance remains a fundamental challenge in machine learning, with traditional solutions often creating as many problems as they solve. We demonstrate that group-aware threshold calibration--setting different decision thresholds for different demographic groups--provides superior robustness compared to synthetic data generation methods. Through extensive experiments, we show that group-specific thresholds achieve 1.5-4% higher balanced accuracy than SMOTE and CT-GAN augmented models while improving worst-group balanced accuracy. Unlike single-threshold approaches that apply one cutoff a","authors_text":"Hunter Gittlin","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T05:57:17Z","title":"Beyond Synthetic Augmentation: Group-Aware Threshold Calibration for Robust Balanced Accuracy in Imbalanced Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02592","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":"sha256:18903b72007fe287e75f87e27fd6ed3ee4c2ab99ce8c58c7029ae62bfae1b492","target":"record","created_at":"2026-07-05T12:03:53Z","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":"2e761a321280c3b5295ec5b316e3f4e1bd2a2053b059fbb44a7fd597eccf60e2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-29T05:57:17Z","title_canon_sha256":"70990b8d43ce1e00f7c432adbd93b6af62cf97c6e8d9d7ea12db925c636ce6f7"},"schema_version":"1.0","source":{"id":"2509.02592","kind":"arxiv","version":1}},"canonical_sha256":"06bcc397ff930fc39f5a801be59e9043ebd021a24e6b3fdf0502cca1da2586bb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"06bcc397ff930fc39f5a801be59e9043ebd021a24e6b3fdf0502cca1da2586bb","first_computed_at":"2026-07-05T12:03:53.931451Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:03:53.931451Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dPC2xaT3HmMWQ0orCa/MchmFz1gGelj7I8KQBomVqNUc2tCnZfl3r7aCxmZyHiVvHY+Imhd1ZkBYFaxbjQybAg==","signature_status":"signed_v1","signed_at":"2026-07-05T12:03:53.931938Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.02592","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18903b72007fe287e75f87e27fd6ed3ee4c2ab99ce8c58c7029ae62bfae1b492","sha256:ffea110b4f10589be5f4ea74a01af98ab211f3d105dd7fcd076db482a119724a"],"state_sha256":"18e4b974f3f353a110f155b98868f6d0581e6a6605f953d43342d91ba2a9c0c5"}