no code implementations • 21 Mar 2024 • Zhe Chen, Heyang Liu, Wenyi Yu, Guangzhi Sun, Hongcheng Liu, Ji Wu, Chao Zhang, Yu Wang, Yanfeng Wang
Although multiple academic video datasets have been constructed and released, few of them support both multimodal content recognition and understanding tasks, which is partially due to the lack of high-quality human annotations.
2 code implementations • 13 Mar 2024 • Yusheng Liao, Yutong Meng, Yuhao Wang, Hongcheng Liu, Yanfeng Wang, Yu Wang
Large Language Models (LLMs) have demonstrated remarkable proficiency in human interactions, yet their application within the medical field remains insufficiently explored.
no code implementations • 19 Feb 2024 • Hongcheng Liu, Pingjie Wang, Yu Wang, Yanfeng Wang
Video-grounded dialogue generation (VDG) requires the system to generate a fluent and accurate answer based on multimodal knowledge.
1 code implementation • 15 Jan 2024 • Yuhao Wang, Yusheng Liao, Heyang Liu, Hongcheng Liu, Yu Wang, Yanfeng Wang
We believe that these hallucinations are partially due to the models' struggle with understanding what they can and cannot perceive from images, a capability we refer to as self-awareness in perception.
no code implementations • 1 Jan 2024 • Hongcheng Liu, Jindong Tong
From the newly established complexity bounds, an important revelation is that the SAA and the canonical stochastic mirror descent (SMD) method, two mainstream solution approaches to SP, entail almost identical rates of sample efficiency, rectifying a long-standing theoretical discrepancy of the SAA from the SMD by the order of $O(d)$.
no code implementations • 26 Sep 2023 • Hongcheng Liu, Zhe Chen, Hui Li, Pingjie Wang, Yanfeng Wang, Yu Wang
Generating dialogue grounded in videos requires a high level of understanding and reasoning about the visual scenes in the videos.
no code implementations • 5 Sep 2023 • Yusheng Liao, Yutong Meng, Hongcheng Liu, Yanfeng Wang, Yu Wang
A medical consultation training set is further constructed to improve the consultation ability of LLMs.
no code implementations • 22 Apr 2021 • Hongcheng Liu, Yu Yang
This paper concerns a convex, stochastic zeroth-order optimization (S-ZOO) problem.
no code implementations • 22 Jul 2020 • Yunmei Chen, Hongcheng Liu, Xiaojing Ye, Qingchao Zhang
We propose a general learning based framework for solving nonsmooth and nonconvex image reconstruction problems.
no code implementations • 15 Mar 2020 • Qingchao Zhang, Xiaojing Ye, Hongcheng Liu, Yun-Mei Chen
Optimization algorithms for solving nonconvex inverse problem have attracted significant interests recently.