collaborators

5 papers

cs.CL2025

Accelerate Speculative Decoding with Sparse Computation in Verification

Jikai Wang, Jianchao Tan, Yuxuan Hu +6

Speculative decoding accelerates autoregressive language model inference by verifying multiple draft tokens in parallel. However, the verification stage often becomes the dominant…

cs.CL2025

CaliDrop: KV Cache Compression with Calibration

Yi Su, Quantong Qiu, Yuechi Zhou +6

Large Language Models (LLMs) require substantial computational resources during generation. While the Key-Value (KV) cache significantly accelerates this process by storing attenti…

cs.CL2025

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework

Zecheng Tang, Haitian Wang, Quantong Qiu +5

Long-context processing has become a fundamental capability for large language models~(LLMs). To assess model's long-context performance, numerous long-context evaluation benchmark…

cs.CL2025

Accurate KV Cache Quantization with Outlier Tokens Tracing

Yi Su, Yuechi Zhou, Quantong Qiu +6

The impressive capabilities of Large Language Models (LLMs) come at the cost of substantial computational resources during deployment. While KV Cache can significantly reduce recom…

cs.CL2025

Alignment-Augmented Speculative Decoding with Alignment Sampling and Conditional Verification

Jikai Wang, Zhenxu Tian, Juntao Li +5

Recent works have revealed the great potential of speculative decoding in accelerating the autoregressive generation process of large language models. The success of these methods…