← Search

Qijun Tan

2 accepted papers

2025

Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs

ICML 2025poster

Existing reinforcement learning (RL) methods for large language models (LLMs) rely on static prompt sets, where prompts are curated a priori, and sampled in a fixed schedule for training, regardless of their usefulness to the RL process. We design `eva`, the first method that allows LLMs to prioriti…

Cited by 0SourcePDFScholar
2023

Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting

EMNLP 2023long main

A crucial challenge for generative large language models (LLMs) is diversity: when a user's prompt is under-specified, models may follow implicit assumptions while generating a response, which may result in homogenization of the responses, as well as certain demographic groups being under-represente…

Cited by 0SourceScholar