no code implementations • 13 Mar 2024 • Ang Li, Qiugen Xiao, Peng Cao, Jian Tang, Yi Yuan, Zijie Zhao, Xiaoyuan Chen, Liang Zhang, Xiangyang Li, Kaitong Yang, Weidong Guo, Yukang Gan, Xu Yu, Daniell Wang, Ying Shan
Using ChatGPT as a labeler to provide feedback on open-domain prompts in RLAIF training, we observe an increase in human evaluators' preference win ratio for model responses, but a decrease in evaluators' satisfaction rate.
1 code implementation • 4 Jan 2024 • Chengyue Wu, Yukang Gan, Yixiao Ge, Zeyu Lu, Jiahao Wang, Ye Feng, Ying Shan, Ping Luo
Humans generally acquire new skills without compromising the old; however, the opposite holds for Large Language Models (LLMs), e. g., from LLaMA to CodeLLaMA.
1 code implementation • 17 Feb 2023 • Yukang Gan, Yixiao Ge, Chang Zhou, Shupeng Su, Zhouchuan Xu, Xuyuan Xu, Quanchao Hui, Xiang Chen, Yexin Wang, Ying Shan
To tackle the challenge, we propose a binary embedding-based retrieval (BEBR) engine equipped with a recurrent binarization algorithm that enables customized bits per dimension.
no code implementations • 30 Oct 2018 • Guanbin Li, Yukang Gan, Hejun Wu, Nong Xiao, Liang Lin
In this paper, we address this problem by developing a Cross-Modal Attentional Context (CMAC) learning framework, which enables the full exploitation of the context information from both RGB and depth data.
no code implementations • ECCV 2018 • Yukang Gan, Xiangyu Xu, Wenxiu Sun, Liang Lin
While significant progress has been made in monocular depth estimation with Convolutional Neural Networks (CNNs) extracting absolute features, such as edges and textures, the depth constraint of neighboring pixels, namely relative features, has been mostly ignored by recent methods.
no code implementations • 15 Jul 2017 • Liang Lin, Lili Huang, Tianshui Chen, Yukang Gan, Hui Cheng
This paper aims at task-oriented action prediction, i. e., predicting a sequence of actions towards accomplishing a specific task under a certain scene, which is a new problem in computer vision research.
1 code implementation • 18 Apr 2016 • Zhen Li, Yukang Gan, Xiaodan Liang, Yizhou Yu, Hui Cheng, Liang Lin
Another long short-term memorized fusion layer is set up to integrate the contexts along the vertical direction from different channels, and perform bi-directional propagation of the fused vertical contexts along the horizontal direction to obtain true 2D global contexts.