10 citations · 14 across the 8 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.CL2026
Self-Verified Distillation: Your Language Model Is Secretly Its Own Synthetic Data Pipeline
Tony Lee, Percy Liang
Can post-trained large language models (LLMs) further improve themselves using only unlabeled prompts, without external teachers or feedback from tools? We study this setting start…
cs.RO2026
RoboReward: General-Purpose Vision-Language Reward Models for Robotics
Tony Lee, Andrew Wagenmaker, Karl Pertsch +3
A well-designed reward is critical for effective reinforcement learning-based policy improvement. In real-world robotics, obtaining such rewards typically requires either labor-int…