23 citations · 39 across the 12 of their papers we have counts for
5 papers · 1 filter
Cost-Aware Contrastive Routing for LLMs
Reza Shirkavand, Shangqian Gao, Peiran Yu +1
We study cost-aware routing for large language models across diverse and dynamic pools of models. Existing approaches often overlook prompt-specific context, rely on expensive mode…
Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
Reza Shirkavand, Peiran Yu, Shangqian Gao +3
Recent advances in diffusion generative models have yielded remarkable progress. While the quality of generated content continues to improve, these models have grown considerably i…
Bregman Gradient Policy Optimization
Feihu Huang, Shangqian Gao, Heng Huang
In the paper, we design a novel Bregman gradient policy optimization framework for reinforcement learning based on Bregman divergences and momentum techniques. Specifically, we pro…
Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds
Feihu Huang, Shangqian Gao
In the paper, we study a class of useful minimax problems on Riemanian manifolds and propose a class of effective Riemanian gradient-based methods to solve these minimax problems.…
Momentum-Based Policy Gradient Methods
Feihu Huang, Shangqian Gao, Jian Pei +1
In the paper, we propose a class of efficient momentum-based policy gradient methods for the model-free reinforcement learning, which use adaptive learning rates and do not require…