3 papers
cs.LG2026
One Model for All: Multi-Objective Controllable Language Models
Qiang He, Yucheng Yang, Tianyi Zhou +3
Aligning large language models (LLMs) with human preferences is critical for enhancing LLMs' safety, helpfulness, humor, faithfulness, etc. Current reinforcement learning from huma…
cs.LG2025
Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
Yucheng Yang, Tianyi Zhou, Qiang He +3
Unsupervised reinforcement learning (URL) aims to learn general skills for unseen downstream tasks. Mutual Information Skill Learning (MISL) addresses URL by maximizing the mutual…
cs.LG2024
Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation
Qiang He, Tianyi Zhou, Meng Fang +1
Representation rank is an important concept for understanding the role of Neural Networks (NNs) in Deep Reinforcement learning (DRL), which measures the expressive capacity of valu…