Assistant Professor, University of Central Florida
3 papers at NeurIPS 2025
We present an efficient judgmetn distribution estimation method for LLM ensembles.
We propose an information-theoretical metric that helps determine the optimal order of demonstrations for in-context learning in large language models.
This paper utilizes multi-agent debate process for llm-as-judge, and employs an adaptive stopping mechanism.
