471 citations · 509 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 36 cited
Large Language Models are Few-Shot Health Learners
Xin Liu, Daniel McDuff, Geza Kovacs +7
Large language models (LLMs) can capture rich representations of concepts that are useful for real-world tasks. However, language alone is limited. While existing LLMs excel at tex…
cs.LG2019★ 2 cited
Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference
Shun Liao, Ting Chen, Tian Lin +2
Computations for the softmax function are significantly expensive when the number of output classes is large. In this paper, we present a novel softmax inference speedup method, Do…
cs.LG2017★ 471 cited
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Yuhuai Wu, Elman Mansimov, Shun Liao +2
In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature. We extend th…