3 papers
cs.LG2025
PAHQ: Accelerating Automated Circuit Discovery through Mixed-Precision Inference Optimization
Xinhai Wang, Shu Yang, Liangyu Wang +4
Circuit discovery, which involves identifying sparse and task-relevant subnetworks in pre-trained language models, is a cornerstone of mechanistic interpretability. Automated Circu…
cs.LG2025
Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models
Liangyu Wang, Huanyi Xie, Xinhai Wang +3
Group-based reinforcement learning algorithms such as Group Reward Policy Optimization (GRPO) have proven effective for fine-tuning large language models (LLMs) with human feedback…
cs.CL2025
Understanding How Value Neurons Shape the Generation of Specified Values in LLMs
Yi Su, Jiayi Zhang, Shu Yang +3
Rapid integration of large language models (LLMs) into societal applications has intensified concerns about their alignment with universal ethical principles, as their internal val…