5 papers
Human-Inspired Multi-Level Reinforcement Learning
Mingkang Wu, Devin White, Vernon Lawhern +2
Reinforcement learning (RL), a common tool in decision making, learns control policies from various experiences based on the associated cumulative return/rewards without treating t…
Multi-Task Reward Learning from Human Ratings
Mingkang Wu, Devin White, Evelyn Rose +3
Reinforcement learning from human feedback (RLHF) has become a key factor in aligning model behavior with users' goals. However, while humans integrate multiple strategies when mak…
Too Big to Think: Capacity, Memorization, and Generalization in Pre-Trained Transformers
Joshua Barron, Devin White
The relationship between memorization and generalization in large language models (LLMs) remains an open area of research, with growing evidence that the two are deeply intertwined…
Performance Optimization of Ratings-Based Reinforcement Learning
Evelyn Rose, Devin White, Mingkang Wu +3
This paper explores multiple optimization methods to improve the performance of rating-based reinforcement learning (RbRL). RbRL, a method based on the idea of human ratings, has b…
Atari-GPT: Benchmarking Multimodal Large Language Models as Low-Level Policies in Atari Games
Nicholas R. Waytowich, Devin White, MD Sunbeam +1
Recent advancements in large language models (LLMs) have expanded their capabilities beyond traditional text-based tasks to multimodal domains, integrating visual, auditory, and te…