16 citations · 16 across the 7 of their papers we have counts for
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cs.LG2026
rePIRL: Learn PRM with Inverse RL for LLM Reasoning
Xian Wu, Kaijie Zhu, Ying Zhang +2
Process rewards have been widely used in deep reinforcement learning to improve training efficiency, reduce variance, and prevent reward hacking. In LLM reasoning, existing works a…
cs.LG2025
PreMoE: Proactive Inference for Efficient Mixture-of-Experts
Zehua Pei, Ying Zhang, Hui-Ling Zhen +6
Mixture-of-Experts (MoE) models offer dynamic computation, but are typically deployed as static full-capacity models, missing opportunities for deployment-specific specialization.…
cs.LG2024★ 16 cited
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
Jay Shah, Ganesh Bikshandi, Ying Zhang +3
Attention, as a core layer of the ubiquitous Transformer architecture, is the bottleneck for large language models and long-context applications. FlashAttention elaborated an appro…