PhD candidate at The Hong Kong Polytechnic University (joint training with EIT, Ningbo), working on reinforcement learning for LLMs and embodied AI. I make the training environment (reward models, verifiers, curricula) measurable and trainable, judged by what each piece does to the model it trains.
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- C3: exact per-decision credit for cooperative LLM agents by transcript replay, with a method-agnostic audit of credit quality. [paper]
- AccuracyParadox-RLHF: reproducible RLHF training and evaluation pipelines and reference reward models. [paper, EMNLP 2024]

