Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification. - Randolph Linderman; Jingyang Zhang; Nathan Inkawhich; Hai Helen Li; Yiran Chen 001 (CoLLAs, 2023)

Mixture Outlier Exposure: Towards Out-of-Distribution Detection in Fine-grained Environments. - Jingyang Zhang; Nathan Inkawhich; Randolph Linderman; Yiran Chen 001; Hai Li 001 (WACV, 2023)

SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection. - Jingyang Zhang; Nathan Inkawhich; Randolph Linderman; Ryan Luley; Yiran Chen 001; Hai Helen Li (CoRR, 2023)

OSR-ViT: A Simple and Modular Framework for Open-Set Object Detection and Discovery. - Matthew Inkawhich; Nathan Inkawhich; Hao Yang 018; Jingyang Zhang; Randolph Linderman; Yiran Chen 001 (IEEE Big Data, 2024)

A Bayesian Nonparametric Perspective on Mahalanobis Distance for Out of Distribution Detection. - Randolph Linderman; Yiran Chen 001; Scott W. Linderman (CoRR, 2025)

SafeTy Reasoning Elicitation Alignment for Multi-Turn Dialogues. - Martin Kuo; Jianyi Zhang; Aolin Ding; Louis DiValentin; Amin Hass; Benjamin F. Morris III; Isaac Jacobson; Randolph Linderman; James Kiessling; Nicolas Ramos; Bhavna Gopal; Maziyar Baran Pouyan; et al. (CoRR, 2025)