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Chengshun Shi

2 accepted papers

2026

From Absolute to Relative: Rethinking Reward Shaping in Group-Based Reinforcement Learning

ICML 2026poster

Reinforcement learning has become a cornerstone for enhancing the reasoning capabilities of Large Language Models, where group-based approaches such as GRPO have emerged as efficient paradigms that optimize policies by leveraging intra-group performance differences. However, these methods typically …

Cited by 0SourceScholar
2024

MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-Tuning

ACL 2024long

Parameter-efficient fine-tuning (PEFT) is a popular method for tailoring pre-trained large language models (LLMs), especially as the models’ scale and the diversity of tasks increase. Low-rank adaptation (LoRA) is based on the idea that the adaptation process is intrinsically low-dimensional, i.e.,…