A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)

PyTorch implementation of our ECCV 2022 paper "Rethinking Confidence Calibration for Failure Prediction"

Promises and Pitfalls of Threshold-based Auto-labeling (NeurIPS 2023, Spotlight)

Pearls from Pebbles: Improved Confidence Functions for Auto-labeling (NeurIPS 2024)

Code for "Budgeted Classification with Rejection: An Evolutionary Method with Multiple Objectives", at IEEE CEC 2022

Robust Selective Classification of Skin Lesions with Asymmetric Costs

Machine Learning with a Reject Option

Longform article reframing abstention (reject option / selective prediction) as product design, not model weakness. Covers coverage as a KPI, calibration as a prerequisite, threshold selection under review capacity and risk, queue/UX design for human-in-the-loop workflows, and anti-patterns that break safety in production.

Decision-safe evaluation + Streamlit dashboard for AI vs Human vs Post-Edited AI text detection. Generates a reliability report card (Accuracy, Macro F1, ECE, Brier), calibration plots, confidence histograms, and a coverage-vs-performance abstention curve. Recommends an operating threshold for human-review routing.

Official implementation of the ICLR paper "Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It"

Code for our paper analyzing the looseness of the upper bound on selective classification performance.