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cs.LG2025
Slow-Fast Policy Optimization: Reposition-Before-Update for LLM Reasoning
Ziyan Wang, Zheng Wang, Xingwei Qu +5
Reinforcement learning (RL) has become central to enhancing reasoning in large language models (LLMs). Yet on-policy algorithms such as Group Relative Policy Optimization (GRPO) of…
cs.LG2024★ 1 cited
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Zhongzhi Yu, Zheng Wang, Yonggan Fu +3
Attention is a fundamental component behind the remarkable achievements of large language models (LLMs). However, our current understanding of the attention mechanism, especially r…
cs.LG2024★ 1 cited
EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting
Zhongzhi Yu, Zheng Wang, Yuhan Li +6
Efficient adaption of large language models (LLMs) on edge devices is essential for applications requiring continuous and privacy-preserving adaptation and inference. However, exis…