1 citations · 2 across the 5 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
Yuhui Li, Fangyun Wei, Chao Zhang +1
The sequential nature of modern LLMs makes them expensive and slow, and speculative sampling has proven to be an effective solution to this problem. Methods like EAGLE perform auto…
cs.CL2024★ 1 cited
EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees
Yuhui Li, Fangyun Wei, Chao Zhang +1
Inference with modern Large Language Models (LLMs) is expensive and time-consuming, and speculative sampling has proven to be an effective solution. Most speculative sampling metho…
cs.CL2024★ 1 cited
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
Yu Du, Fangyun Wei, Hongyang Zhang
We introduce AnyTool, a large language model agent designed to revolutionize the utilization of a vast array of tools in addressing user queries. We utilize over 16,000 APIs from R…