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 • 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
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
We also developed a training mechanism, MocoRank, to handle the intra-class variation, the ordinal relationship between different classes, and the data imbalance problem.
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