1 code implementation • 8 Apr 2024 • Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu, Xiyan Shao, Xinyuan Wang, Shuhua Xie, Haodi Ma, Adithya Samavedhi, Qiyue Gao, Zhen Wang, Zhiting Hu
(2) We develop LLM Reasoners, a library for standardized modular implementation of existing and new reasoning algorithms, under a unified formulation of the search, reward, and world model components.
1 code implementation • 8 Mar 2024 • Weibin Liao, Yinghao Zhu, Xinyuan Wang, Chengwei Pan, Yasha Wang, Liantao Ma
This highlights the potential of Mamba in facilitating model lightweighting.
1 code implementation • 6 Mar 2024 • Xinyuan Wang, Dongjie Wang, Wangyang Ying, Rui Xie, Haifeng Chen, Yanjie Fu
A deep Q-network, pre-trained with the original features and their corresponding pseudo labels, is employed to improve the efficacy of the exploration process in feature selection.
1 code implementation • 14 Feb 2024 • Xinyuan Wang, Liang Wu, Liangjie Hong, Hao liu, Yanjie Fu
Additionally, we introduce graph relationship understanding and analysis functions into LLMs to enhance their focus on connectivity information in graph data.
no code implementations • 11 Jan 2024 • Xinyuan Wang, Chengwei Pan, Hongming Dai, Gangming Zhao, Jinpeng Li, Xiao Zhang, Yizhou Yu
In this study, we leverage Fourier domain learning as a substitute for multi-scale convolutional kernels in 3D hierarchical segmentation models, which can reduce computational expenses while preserving global receptive fields within the network.
1 code implementation • 14 Dec 2023 • Xingrun Xing, Li Du, Xinyuan Wang, Xianlin Zeng, Yequan Wang, Zheng Zhang, Jiajun Zhang
Specifically, we first analyze the binarization error in self-attention operations and derive the polynomials of binarization error.
no code implementations • 26 Nov 2023 • Xinyuan Wang, Changqing Su, Bo Xiong
Sparse-view CT reconstruction, aimed at reducing X-ray radiation risks, frequently suffers from image quality degradation, manifested as noise and artifacts.
1 code implementation • 25 Oct 2023 • Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
Highly effective, task-specific prompts are often heavily engineered by experts to integrate detailed instructions and domain insights based on a deep understanding of both instincts of large language models (LLMs) and the intricacies of the target task.
no code implementations • 13 Oct 2023 • Harsh Kumar, Ilya Musabirov, Mohi Reza, Jiakai Shi, Xinyuan Wang, Joseph Jay Williams, Anastasia Kuzminykh, Michael Liut
Personalized chatbot-based teaching assistants can be crucial in addressing increasing classroom sizes, especially where direct teacher presence is limited.