Papers by Yuechi Zhou
Accurate KV Cache Quantization with Outlier Tokens Tracing (2025.acl-long)
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Yi Su, Yuechi Zhou, Quantong Qiu, Juntao Li, Qingrong Xia, Ping Li, Xinyu Duan, Zhefeng Wang, Min Zhang
| Challenge: | Large Language Models (LLMs) require substantial computational resources during deployment. |
| Approach: | They propose a method to identify outlier tokens and exclude them from quantization . they find that the method can deliver a 6.4 times reduction in memory usage and a 2.5 times increase in throughput . |
| Outcome: | The proposed method delivers a 6.4 times reduction in memory usage and a 2.5 times increase in throughput under 2-bit quantization. |
ALW: Adaptive Layer-Wise contrastive decoding enhancing reasoning ability in Large Language Models (2025.findings-acl)
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| Challenge: | Existing research has demonstrated that contrast decoding of two different models can improve text quality in open-ended text generation but with limited gains on reasoning tasks. |
| Approach: | They propose a framework that dynamically disentangles noise in shallow layers from critical signals in deep layers to enhance reasoning ability. |
| Outcome: | The proposed framework improves answer accuracy while maintaining inference efficiency. |