Xiaodong Liu

MoEs can be pruned more effectively by considering cross-layer redundancy, leading to significant performance gains compared to uniform pruning strategies.

AgentOS reimagines LLMs as reasoning kernels within a structured OS, offering a blueprint for more robust and scalable AI agents.

Forget full-cache rollouts: this parameter-efficient fine-tuning method lets large reasoning models maintain accuracy while slashing memory usage during RL training.