Representation Engineering: A Top-Down Approach to AI Transparency. - Andy Zou; Long Phan; Sarah Li Chen; James Campbell; Phillip Guo; Richard Ren; Alexander Pan; Xuwang Yin; Mantas Mazeika; Ann-Kathrin Dombrowski; Shashwat Goel; Nathaniel Li; et al. (CoRR, 2023)

Localizing Lying in Llama: Understanding Instructed Dishonesty on True-False Questions Through Prompting, Probing, and Patching. - James Campbell; Richard Ren; Phillip Guo (CoRR, 2023)

Deep Reinforcement Learning for Decentralized Multi-Robot Exploration With Macro Actions. - Aaron Hao Tan; Federico Pizarro Bejarano; Yuhan Zhu; Richard Ren; Goldie Nejat (IEEE Robotics Autom. Lett., 2023)

Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? - Richard Ren; Steven Basart; Adam Khoja; Alice Gatti; Long Phan; Xuwang Yin; Mantas Mazeika; Alexander Pan; Gabriel Mukobi; Ryan H. Kim; Stephen Fitz; Dan Hendrycks (NeurIPS, 2024)

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs. - Mantas Mazeika; Xuwang Yin; Rishub Tamirisa; Jaehyuk Lim; Bruce W. Lee; Richard Ren; Long Phan; Norman Mu; Adam Khoja; Oliver Zhang; Dan Hendrycks (CoRR, 2025)

The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems. - Richard Ren; Arunim Agarwal; Mantas Mazeika; Cristina Menghini; Robert Vacareanu; Brad Kenstler; Mick Yang; Isabelle Barrass; Alice Gatti; Xuwang Yin; Eduardo Trevino; Matias Geralnik; et al. (CoRR, 2025)