1 code implementation • 26 May 2024 • Xijie Huang, Xinyuan Wang, Hantao Zhang, Jiawen Xi, Jingkun An, Hao Wang, Chengwei Pan
Security concerns related to Large Language Models (LLMs) have been extensively explored, yet the safety implications for Multimodal Large Language Models (MLLMs), particularly in medical contexts (MedMLLMs), remain insufficiently studied.
1 code implementation • 28 Mar 2024 • Pingcheng Dong, Yonghao Tan, Dong Zhang, Tianwei Ni, Xuejiao Liu, Yu Liu, Peng Luo, Luhong Liang, Shih-Yang Liu, Xijie Huang, Huaiyu Zhu, Yun Pan, Fengwei An, Kwang-Ting Cheng
Non-linear functions are prevalent in Transformers and their lightweight variants, incurring substantial and frequently underestimated hardware costs.
no code implementations • 14 Dec 2023 • Chi-Hsuan Wu, Shih-Yang Liu, Xijie Huang, Xingbo Wang, Rong Zhang, Luca Minciullo, Wong Kai Yiu, Kenny Kwan, Kwang-Ting Cheng
However, a major doubt about online learning is whether students are as engaged as they are in face-to-face classes.
no code implementations • 14 Dec 2023 • Xijie Huang, Li Lyna Zhang, Kwang-Ting Cheng, Fan Yang, Mao Yang
In this work, we propose CoT-Influx, a novel approach that pushes the boundary of few-shot Chain-of-Thoughts (CoT) learning to improve LLM mathematical reasoning.
Ranked #106 on Arithmetic Reasoning on GSM8K
1 code implementation • 25 Oct 2023 • Shih-Yang Liu, Zechun Liu, Xijie Huang, Pingcheng Dong, Kwang-Ting Cheng
Our method, for the first time, can quantize both weights and activations in the LLaMA-13B to only 4-bit and achieves an average score of 63. 1 on the common sense zero-shot reasoning tasks, which is only 5. 8 lower than the full-precision model, significantly outperforming the previous state-of-the-art by 12. 7 points.
no code implementations • 1 Aug 2023 • Jianben He, Xingbo Wang, Kam Kwai Wong, Xijie Huang, Changjian Chen, Zixin Chen, Fengjie Wang, Min Zhu, Huamin Qu
Constructing supervised machine learning models for real-world video analysis require substantial labeled data, which is costly to acquire due to scarce domain expertise and laborious manual inspection.
1 code implementation • 1 Jul 2023 • Xijie Huang, Zhiqiang Shen, Kwang-Ting Cheng
We also find that the variations in ViTs cause training oscillations, bringing instability during quantization-aware training (QAT).
1 code implementation • 12 Jun 2023 • Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng
Compared with previous coreset selection methods, our method significantly improves QAT performance with different dataset fractions.
no code implementations • 9 Jun 2022 • Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric Xing, Kwang-Ting Cheng
In order to deploy deep models in a computationally efficient manner, model quantization approaches have been frequently used.
1 code implementation • 4 May 2022 • Jeffry Wicaksana, Zengqiang Yan, Dong Zhang, Xijie Huang, Huimin Wu, Xin Yang, Kwang-Ting Cheng
To relax this assumption, in this work, we propose a label-agnostic unified federated learning framework, named FedMix, for medical image segmentation based on mixed image labels.
1 code implementation • 25 Jan 2021 • Yong-Lu Li, Xinpeng Liu, Xiaoqian Wu, Xijie Huang, Liang Xu, Cewu Lu
Human-Object Interaction (HOI) detection is an important problem to understand how humans interact with objects.
Ranked #28 on Human-Object Interaction Detection on V-COCO
2 code implementations • CVPR 2020 • Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Shiyi Wang, Hao-Shu Fang, Ze Ma, Mingyang Chen, Cewu Lu
In light of this, we propose a new path: infer human part states first and then reason out the activities based on part-level semantics.
Ranked #3 on Human-Object Interaction Detection on HICO
no code implementations • 18 Nov 2019 • Xijie Huang, Moustafa Alzantot, Mani Srivastava
NeuronInspect first identifies the existence of backdoor attack targets by generating the explanation heatmap of the output layer.
4 code implementations • 13 Apr 2019 • Yong-Lu Li, Liang Xu, Xinpeng Liu, Xijie Huang, Yue Xu, Mingyang Chen, Ze Ma, Shiyi Wang, Hao-Shu Fang, Cewu Lu
To address these and promote the activity understanding, we build a large-scale Human Activity Knowledge Engine (HAKE) based on the human body part states.
Ranked #2 on Human-Object Interaction Detection on HICO (using extra training data)
3 code implementations • CVPR 2019 • Yong-Lu Li, Siyuan Zhou, Xijie Huang, Liang Xu, Ze Ma, Hao-Shu Fang, Yan-Feng Wang, Cewu Lu
On account of the generalization of interactiveness, interactiveness network is a transferable knowledge learner and can be cooperated with any HOI detection models to achieve desirable results.
Ranked #29 on Human-Object Interaction Detection on V-COCO