From the 2 of 8 linked papers with an AI index.
1 citations · 1 across the 3 of their papers we have counts for
8 papers
CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning
Songqiao Su, Xiaoya Li, Albert Wang +3
In this paper, we propose CUDA-L2, a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multi…
CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search
Xiaoya Li, Albert Wang, Guoyin Wang +2
The paper introduces CRINN, a contrastive reinforcement learning framework that automatically designs faster approximate nearest‑neighbor search algorithms while respecting accurac…
CUDA-L1: Improving CUDA Optimization via Contrastive Reinforcement Learning
Xiaoya Li, Albert Wang, Guoyin Wang +2
The paper presents CUDA-L1, a reinforcement learning system that automatically optimizes CUDA code using a contrastive RL algorithm, achieving large speedups on GPU kernels without…
Instruction Tuning for Large Language Models: A Survey
Shengyu Zhang, Linfeng Dong, Xiaoya Li +8
This paper surveys research works in the quickly advancing field of instruction tuning (IT), which can also be referred to as supervised fine-tuning (SFT)\footnote{In this paper, u…
FaceID-6M: A Large-Scale, Open-Source FaceID Customization Dataset
Shuhe Wang, Xiaoya Li, Jiwei Li +8
Due to the data-driven nature of current face identity (FaceID) customization methods, all state-of-the-art models rely on large-scale datasets containing millions of high-quality…
Reinforcement Learning Enhanced LLMs: A Survey
Shuhe Wang, Shengyu Zhang, Jie Zhang +7
Reinforcement learning (RL) enhanced large language models (LLMs), particularly exemplified by DeepSeek-R1, have exhibited outstanding performance. Despite the effectiveness in imp…