Fanzeng Xia

Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents

In-Context Reinforcement Learning (ICRL) is a frontier paradigm to solve Reinforcement Learning (RL) problems in the foundation-model era. While ICRL capabilities have been demonstrated in transformers through task-specific training, the potential of large language models (LLMs) out of the box remai…