4 papers
Scheduling LLM Inference with Uncertainty-Aware Output Length Predictions
Haoyu Zheng, Yongqiang Zhang, Fangcheng Fu +7
To schedule LLM inference, the \textit{shortest job first} (SJF) principle is favorable by prioritizing requests with short output lengths to avoid head-of-line (HOL) blocking. Exi…
Can Large Language Models Reinvent Foundational Algorithms?
Jian Zhao, Haoren Luo, Yu Wang +3
LLMs have shown strong potential to advance scientific discovery. Whether they possess the capacity for foundational innovation, however, remains an open question. In this work, we…
How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG
Qiming Zeng, Xiao Yan, Hao Luo +7
By retrieving contexts from knowledge graphs, graph-based retrieval-augmented generation (GraphRAG) enhances large language models (LLMs) to generate quality answers for user quest…
Guiding LLM-based Smart Contract Generation with Finite State Machine
Hao Luo, Yuhao Lin, Xiao Yan +5
Smart contract is a kind of self-executing code based on blockchain technology with a wide range of application scenarios, but the traditional generation method relies on manual co…