3 papers
cs.LG2025
Reasoning Language Model Inference Serving Unveiled: An Empirical Study
Qi Li, Junpan Wu, Xiang Liu +6
The reasoning large language model (RLLM) has been proven competitive in solving complex reasoning tasks such as mathematics, coding, compared to general LLM. However, the serving…
cs.DC2025
BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems
Yuxin Wang, Yuhan Chen, Zeyu Li +11
Serving systems for Large Language Models (LLMs) are often optimized to improve quality of service (QoS) and throughput. However, due to the lack of open-source LLM serving workloa…
cs.LG2024
STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs
Peijie Dong, Lujun Li, Yuedong Zhong +8
In this paper, we present the first structural binarization method for LLM compression to less than 1-bit precision. Although LLMs have achieved remarkable performance, their memor…