no code implementations • 19 May 2024 • Haoyuan Sun, Zihao Wu, Bo Xia, Pu Chang, Zibin Dong, Yifu Yuan, Yongzhe Chang, Xueqian Wang
EAFO methodology presents a novel perspective for designing static activation functions in deep neural networks and the potential of dynamically optimizing activation during iterative training.
1 code implementation • 19 Mar 2024 • Chong Ma, Hanqi Jiang, WenTing Chen, Zihao Wu, Xiaowei Yu, Fang Zeng, Lei Guo, Dajiang Zhu, Tuo Zhang, Dinggang Shen, Tianming Liu, Xiang Li
Additionally, we explore the impact of varying amounts of eye-gaze data on model performance, highlighting the feasibility and utility of integrating this auxiliary data into multi-modal pre-training.
no code implementations • 26 Feb 2024 • Yu Ming, Zihao Wu, Jie Yang, Danyi Li, Yuan Gao, Changxin Gao, Gui-Song Xia, Yuanqing Li, Li Liang, Jin-Gang Yu
In this paper, we propose to formulate annotation-efficient nucleus instance segmentation from the perspective of few-shot learning (FSL).
no code implementations • 17 Feb 2024 • Shaochen Xu, Zihao Wu, Huaqin Zhao, Peng Shu, Zhengliang Liu, Wenxiong Liao, Sheng Li, Andrea Sikora, Tianming Liu, Xiang Li
In this study, we leverage LLM to enhance the semantic analysis and develop similarity metrics for texts, addressing the limitations of traditional unsupervised NLP metrics like ROUGE and BLEU.
no code implementations • 9 Feb 2024 • Peng Shu, Huaqin Zhao, Hanqi Jiang, Yiwei Li, Shaochen Xu, Yi Pan, Zihao Wu, Zhengliang Liu, Guoyu Lu, Le Guan, Gong Chen, Xianqiao Wang Tianming Liu
To teach young children how to code and compete in robot challenges, large language models are being utilized for robot code explanation, generation, and modification.
no code implementations • 22 Jan 2024 • Huaqin Zhao, Zhengliang Liu, Zihao Wu, Yiwei Li, Tianze Yang, Peng Shu, Shaochen Xu, Haixing Dai, Lin Zhao, Gengchen Mai, Ninghao Liu, Tianming Liu
Additionally, we conducted holistic tests on multiple financial tasks through the combination of natural language instructions.
no code implementations • 13 Jan 2024 • Jie Tian, Jixin Hou, Zihao Wu, Peng Shu, Zhengliang Liu, Yujie Xiang, Beikang Gu, Nicholas Filla, Yiwei Li, Ning Liu, Xianyan Chen, Keke Tang, Tianming Liu, Xianqiao Wang
This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering with a focus on mechanics.
no code implementations • 9 Jan 2024 • Jiaqi Wang, Zihao Wu, Yiwei Li, Hanqi Jiang, Peng Shu, Enze Shi, Huawen Hu, Chong Ma, Yiheng Liu, Xuhui Wang, Yincheng Yao, Xuan Liu, Huaqin Zhao, Zhengliang Liu, Haixing Dai, Lin Zhao, Bao Ge, Xiang Li, Tianming Liu, Shu Zhang
Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions.
no code implementations • 4 Jan 2024 • Yiheng Liu, Hao He, Tianle Han, Xu Zhang, Mengyuan Liu, Jiaming Tian, Yutong Zhang, Jiaqi Wang, Xiaohui Gao, Tianyang Zhong, Yi Pan, Shaochen Xu, Zihao Wu, Zhengliang Liu, Xin Zhang, Shu Zhang, Xintao Hu, Tuo Zhang, Ning Qiang, Tianming Liu, Bao Ge
Low-cost training and deployment of LLMs represent the future development trend.
no code implementations • 23 Dec 2023 • Chenjiao Tan, Qian Cao, Yiwei Li, Jielu Zhang, Xiao Yang, Huaqin Zhao, Zihao Wu, Zhengliang Liu, Hao Yang, Nemin Wu, Tao Tang, Xinyue Ye, Lilong Chai, Ninghao Liu, Changying Li, Lan Mu, Tianming Liu, Gengchen Mai
The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision.
no code implementations • 10 Dec 2023 • Gyeong-Geon Lee, Lehong Shi, Ehsan Latif, Yizhu Gao, Arne Bewersdorff, Matthew Nyaaba, Shuchen Guo, Zihao Wu, Zhengliang Liu, Hui Wang, Gengchen Mai, Tiaming Liu, Xiaoming Zhai
This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intelligence (AGI) in educational contexts.
no code implementations • 8 Dec 2023 • Hui Wang, Anh Dang, Zihao Wu, Son Mac
The advancements in Generative Artificial Intelligence (GenAI) technologies such as ChatGPT provide opportunities to enrich educational experiences, but also raise concerns about academic integrity if misused.
no code implementations • 8 Dec 2023 • Huan Zhao, Qian Ling, Yi Pan, Tianyang Zhong, Jin-Yu Hu, Junjie Yao, Fengqian Xiao, Zhenxiang Xiao, Yutong Zhang, San-Hua Xu, Shi-Nan Wu, Min Kang, Zihao Wu, Zhengliang Liu, Xi Jiang, Tianming Liu, Yi Shao
In recent years, pre-trained large language models (LLMs) have achieved tremendous success in the field of Natural Language Processing (NLP).
no code implementations • 10 Nov 2023 • Zhengliang Liu, Hanqi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yiwei Li, Xiaowei Yu, Yutong Zhang, Yi Pan, Peng Shu, Yanjun Lyu, Lu Zhang, Junjie Yao, Peixin Dong, Chao Cao, Zhenxiang Xiao, Jiaqi Wang, Huan Zhao, Shaochen Xu, Yaonai Wei, Jingyuan Chen, Haixing Dai, Peilong Wang, Hao He, Zewei Wang, Xinyu Wang, Xu Zhang, Lin Zhao, Yiheng Liu, Kai Zhang, Liheng Yan, Lichao Sun, Jun Liu, Ning Qiang, Bao Ge, Xiaoyan Cai, Shijie Zhao, Xintao Hu, Yixuan Yuan, Gang Li, Shu Zhang, Xin Zhang, Xi Jiang, Tuo Zhang, Dinggang Shen, Quanzheng Li, Wei Liu, Xiang Li, Dajiang Zhu, Tianming Liu
GPT-4V represents a breakthrough in artificial general intelligence (AGI) for computer vision, with applications in the biomedical domain.
no code implementations • 7 Nov 2023 • Jason Holmes, Rui Peng, Yiwei Li, Jinyu Hu, Zhengliang Liu, Zihao Wu, Huan Zhao, Xi Jiang, Wei Liu, Hong Wei, Jie Zou, Tianming Liu, Yi Shao
IMPORTANCE The response effectiveness of different large language models (LLMs) and various individuals, including medical students, graduate students, and practicing physicians, in pediatric ophthalmology consultations, has not been clearly established yet.
no code implementations • 7 Nov 2023 • Jason Holmes, Shuyuan Ye, Yiwei Li, Shi-Nan Wu, Zhengliang Liu, Zihao Wu, Jinyu Hu, Huan Zhao, Xi Jiang, Wei Liu, Hong Wei, Jie Zou, Tianming Liu, Yi Shao
Methods: A 100-item ophthalmology single-choice test was administered to three different LLMs (GPT-3. 5, GPT-4, and PaLM2) and three different professional levels (medical undergraduates, medical masters, and attending physicians), respectively.
no code implementations • 5 Nov 2023 • Xinyu Gong, Jason Holmes, Yiwei Li, Zhengliang Liu, Qi Gan, Zihao Wu, Jianli Zhang, Yusong Zou, Yuxi Teng, Tian Jiang, Hongtu Zhu, Wei Liu, Tianming Liu, Yajun Yan
Recent advances in Large Language Models (LLMs) have presented new opportunities for integrating Artificial General Intelligence (AGI) into biological research and education.
no code implementations • 30 Oct 2023 • Zhengliang Liu, Yiwei Li, Qian Cao, Junwen Chen, Tianze Yang, Zihao Wu, John Hale, John Gibbs, Khaled Rasheed, Ninghao Liu, Gengchen Mai, Tianming Liu
Recent advances in artificial general intelligence (AGI), particularly large language models and creative image generation systems have demonstrated impressive capabilities on diverse tasks spanning the arts and humanities.
no code implementations • 19 Oct 2023 • David Liu, Zhengkun Li, Zihao Wu, Changying Li
This work specifically tackles the first challenge by proposing a novel Digital-Twin(DT)MARS-CycleGAN model for image augmentation to improve our Modular Agricultural Robotic System (MARS)'s crop object detection from complex and variable backgrounds.
no code implementations • 8 Oct 2023 • Tianyang Zhong, Wei Zhao, Yutong Zhang, Yi Pan, Peixin Dong, Zuowei Jiang, Xiaoyan Kui, Youlan Shang, Li Yang, Yaonai Wei, Longtao Yang, Hao Chen, Huan Zhao, Yuxiao Liu, Ning Zhu, Yiwei Li, Yisong Wang, Jiaqi Yao, Jiaqi Wang, Ying Zeng, Lei He, Chao Zheng, Zhixue Zhang, Ming Li, Zhengliang Liu, Haixing Dai, Zihao Wu, Lu Zhang, Shu Zhang, Xiaoyan Cai, Xintao Hu, Shijie Zhao, Xi Jiang, Xin Zhang, Xiang Li, Dajiang Zhu, Lei Guo, Dinggang Shen, Junwei Han, Tianming Liu, Jun Liu, Tuo Zhang
Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels.
no code implementations • 19 Sep 2023 • Chenhao Tang, Zhengliang Liu, Chong Ma, Zihao Wu, Yiwei Li, Wei Liu, Dajiang Zhu, Quanzheng Li, Xiang Li, Tianming Liu, Lei Fan
In this study, we investigate a privacy policy text analysis framework PolicyGPT based on the LLM.
no code implementations • 14 Sep 2023 • Fei Dou, Jin Ye, Geng Yuan, Qin Lu, Wei Niu, Haijian Sun, Le Guan, Guoyu Lu, Gengchen Mai, Ninghao Liu, Jin Lu, Zhengliang Liu, Zihao Wu, Chenjiao Tan, Shaochen Xu, Xianqiao Wang, Guoming Li, Lilong Chai, Sheng Li, Jin Sun, Hongyue Sun, Yunli Shao, Changying Li, Tianming Liu, WenZhan Song
Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas.
no code implementations • 29 Aug 2023 • Zhengliang Liu, Yiwei Li, Peng Shu, Aoxiao Zhong, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Jie Luo, Cheng Chen, Sekeun Kim, Jiang Hu, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Tianming Liu, Quanzheng Li, Xiang Li
This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning.
1 code implementation • 25 Jul 2023 • Zhengliang Liu, Tianyang Zhong, Yiwei Li, Yutong Zhang, Yi Pan, Zihao Zhao, Peixin Dong, Chao Cao, Yuxiao Liu, Peng Shu, Yaonai Wei, Zihao Wu, Chong Ma, Jiaqi Wang, Sheng Wang, Mengyue Zhou, Zuowei Jiang, Chunlin Li, Jason Holmes, Shaochen Xu, Lu Zhang, Haixing Dai, Kai Zhang, Lin Zhao, Yuanhao Chen, Xu Liu, Peilong Wang, Pingkun Yan, Jun Liu, Bao Ge, Lichao Sun, Dajiang Zhu, Xiang Li, Wei Liu, Xiaoyan Cai, Xintao Hu, Xi Jiang, Shu Zhang, Xin Zhang, Tuo Zhang, Shijie Zhao, Quanzheng Li, Hongtu Zhu, Dinggang Shen, Tianming Liu
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP).
no code implementations • 21 Jul 2023 • Zihan Guan, Zihao Wu, Zhengliang Liu, Dufan Wu, Hui Ren, Quanzheng Li, Xiang Li, Ninghao Liu
Participant recruitment based on unstructured medical texts such as clinical notes and radiology reports has been a challenging yet important task for the cohort establishment in clinical research.
no code implementations • 19 Jul 2023 • Zhengliang Liu, Zihao Wu, Mengxuan Hu, Bokai Zhao, Lin Zhao, Tianyi Zhang, Haixing Dai, Xianyan Chen, Ye Shen, Sheng Li, Brian Murray, Tianming Liu, Andrea Sikora
In this study, we introduce PharmacyGPT, a novel framework to assess the capabilities of large language models (LLMs) such as ChatGPT and GPT-4 in emulating the role of clinical pharmacists.
no code implementations • 10 Jul 2023 • Haixing Dai, Lu Zhang, Lin Zhao, Zihao Wu, Zhengliang Liu, David Liu, Xiaowei Yu, Yanjun Lyu, Changying Li, Ninghao Liu, Tianming Liu, Dajiang Zhu
With the popularity of deep neural networks (DNNs), model interpretability is becoming a critical concern.
1 code implementation • 5 Jul 2023 • Hongmin Cai, Xiaoke Huang, Zhengliang Liu, Wenxiong Liao, Haixing Dai, Zihao Wu, Dajiang Zhu, Hui Ren, Quanzheng Li, Tianming Liu, Xiang Li
As AD impairs the patient's language understanding and expression ability, the speech of AD patients can serve as an indicator of this disease.
1 code implementation • 3 Jul 2023 • Haixing Dai, Chong Ma, Zhiling Yan, Zhengliang Liu, Enze Shi, Yiwei Li, Peng Shu, Xiaozheng Wei, Lin Zhao, Zihao Wu, Fang Zeng, Dajiang Zhu, Wei Liu, Quanzheng Li, Lichao Sun, Shu Zhang Tianming Liu, Xiang Li
Starting with an initial point prompt, SAM produces an initial mask, which is then fed into our proposed SAMAug to generate augmented point prompts.
no code implementations • 3 Jul 2023 • Jiaqi Wang, Zhengliang Liu, Lin Zhao, Zihao Wu, Chong Ma, Sigang Yu, Haixing Dai, Qiushi Yang, Yiheng Liu, Songyao Zhang, Enze Shi, Yi Pan, Tuo Zhang, Dajiang Zhu, Xiang Li, Xi Jiang, Bao Ge, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang
This review aims to summarize the methods employed in the computer vision domain for large vision models and visual prompt engineering, exploring the latest advancements in visual prompt engineering.
no code implementations • 20 Jun 2023 • Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, Sheng Li
ChatGPT has shown to be a strong baseline in many NLP tasks, and we believe it has the potential to improve our model in the task of semantic matching and enhance our model's understanding of food-related concepts and relationships.
no code implementations • 20 Jun 2023 • Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, Dajiang Zhu, Tianming Liu, Wei Liu
Given that SAM, a model pre-trained purely on natural images, can handle the delineation of OARs from medical images with clinically acceptable accuracy, these results highlight SAM's robust generalization capabilities with consistent accuracy in automatic segmentation for radiotherapy.
no code implementations • 16 Jun 2023 • Haixing Dai, Yiwei Li, Zhengliang Liu, Lin Zhao, Zihao Wu, Suhang Song, Ye Shen, Dajiang Zhu, Xiang Li, Sheng Li, Xiaobai Yao, Lu Shi, Quanzheng Li, Zhuo Chen, Donglan Zhang, Gengchen Mai, Tianming Liu
In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT which can conduct data collection, processing, and analysis about complex health narratives of Alzheimer's Disease in an autonomous manner via users' textual prompts.
no code implementations • 14 Jun 2023 • Zhengliang Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, Haixing Dai, Lin Zhao, Lichao Sun, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Xiang Li, Quanzheng Li, Tianming Liu
We introduce Radiology-GPT, a large language model for radiology.
no code implementations • 8 Jun 2023 • Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkun Yan, Quanzheng Li, Wei Liu, Tianming Liu, Dinggang Shen
In this review, we explore the potential applications of Artificial General Intelligence (AGI) models in healthcare, focusing on foundational Large Language Models (LLMs), Large Vision Models, and Large Multimodal Models.
no code implementations • 17 May 2023 • Xiao Yang, Haixing Dai, Zihao Wu, Ramesh Bist, Sachin Subedi, Jin Sun, Guoyu Lu, Changying Li, Tianming Liu, Lilong Chai
This study aims to assess the zero-shot segmentation performance of SAM on representative chicken segmentation tasks, including part-based segmentation and the use of infrared thermal images, and to explore chicken-tracking tasks by using SAM as a segmentation tool.
no code implementations • 29 Apr 2023 • Zhenxiang Xiao, Yuzhong Chen, Lu Zhang, Junjie Yao, Zihao Wu, Xiaowei Yu, Yi Pan, Lin Zhao, Chong Ma, Xinyu Liu, Wei Liu, Xiang Li, Yixuan Yuan, Dinggang Shen, Dajiang Zhu, Tianming Liu, Xi Jiang
Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downstream tasks.
no code implementations • 28 Apr 2023 • Jiaqi Wang, Enze Shi, Sigang Yu, Zihao Wu, Chong Ma, Haixing Dai, Qiushi Yang, Yanqing Kang, Jinru Wu, Huawen Hu, Chenxi Yue, Haiyang Zhang, Yiheng Liu, Yi Pan, Zhengliang Liu, Lichao Sun, Xiang Li, Bao Ge, Xi Jiang, Dajiang Zhu, Yixuan Yuan, Dinggang Shen, Tianming Liu, Shu Zhang
Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aiming to enhance their performance on specific tasks.
no code implementations • 23 Apr 2023 • Wenxiong Liao, Zhengliang Liu, Haixing Dai, Shaochen Xu, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Dajiang Zhu, Hongmin Cai, Tianming Liu, Xiang Li
We focus on analyzing the differences between medical texts written by human experts and generated by ChatGPT, and designing machine learning workflows to effectively detect and differentiate medical texts generated by ChatGPT.
no code implementations • 21 Apr 2023 • Tianyang Zhong, Yaonai Wei, Li Yang, Zihao Wu, Zhengliang Liu, Xiaozheng Wei, Wenjun Li, Junjie Yao, Chong Ma, Xiang Li, Dajiang Zhu, Xi Jiang, Junwei Han, Dinggang Shen, Tianming Liu, Tuo Zhang
The proposed method uses the strengths of LLMs' understanding and logical reasoning to correct the incomplete logical facts for optimizing the performance of perceptual module, by summarizing and reorganizing reasoning rules represented in natural language format.
no code implementations • 18 Apr 2023 • Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Haixing Dai, Chong Ma, Zhengliang Liu, Lin Zhao, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu
To this end, in this study, we evaluate the performance of ChatGPT/GPT-4 on a radiology NLI task and compare it to other models fine-tuned specifically on task-related data samples.
2 code implementations • 17 Apr 2023 • Chong Ma, Zihao Wu, Jiaqi Wang, Shaochen Xu, Yaonai Wei, Fang Zeng, Zhengliang Liu, Xi Jiang, Lei Guo, Xiaoyan Cai, Shu Zhang, Tuo Zhang, Dajiang Zhu, Dinggang Shen, Tianming Liu, Xiang Li
The 'Impression' section of a radiology report is a critical basis for communication between radiologists and other physicians, and it is typically written by radiologists based on the 'Findings' section.
no code implementations • 4 Apr 2023 • Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Lin Zhao, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, Bao Ge
This paper presents a comprehensive survey of ChatGPT-related (GPT-3. 5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains.
no code implementations • 28 Mar 2023 • Lin Zhao, Lu Zhang, Zihao Wu, Yuzhong Chen, Haixing Dai, Xiaowei Yu, Zhengliang Liu, Tuo Zhang, Xintao Hu, Xi Jiang, Xiang Li, Dajiang Zhu, Dinggang Shen, Tianming Liu
Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do.
no code implementations • 27 Mar 2023 • Xu Liu, Mengyue Zhou, Gaosheng Shi, Yu Du, Lin Zhao, Zihao Wu, David Liu, Tianming Liu, Xintao Hu
Linking computational natural language processing (NLP) models and neural responses to language in the human brain on the one hand facilitates the effort towards disentangling the neural representations underpinning language perception, on the other hand provides neurolinguistics evidence to evaluate and improve NLP models.
no code implementations • 27 Mar 2023 • Xiaowei Yu, Lu Zhang, Haixing Dai, Yanjun Lyu, Lin Zhao, Zihao Wu, David Liu, Tianming Liu, Dajiang Zhu
Designing more efficient, reliable, and explainable neural network architectures is critical to studies that are based on artificial intelligence (AI) techniques.
no code implementations • 27 Mar 2023 • Lin Zhao, Haixing Dai, Zihao Wu, Dajiang Zhu, Tianming Liu
In this study, We explore a novel brain-inspired design principle based on the core-periphery property of the human brain network to guide the design of CNNs.
1 code implementation • 20 Mar 2023 • Zhengliang Liu, Yue Huang, Xiaowei Yu, Lu Zhang, Zihao Wu, Chao Cao, Haixing Dai, Lin Zhao, Yiwei Li, Peng Shu, Fang Zeng, Lichao Sun, Wei Liu, Dinggang Shen, Quanzheng Li, Tianming Liu, Dajiang Zhu, Xiang Li
The digitization of healthcare has facilitated the sharing and re-using of medical data but has also raised concerns about confidentiality and privacy.
no code implementations • 25 Feb 2023 • Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Yihan Cao, Zihao Wu, Lin Zhao, Shaochen Xu, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Lichao Sun, Quanzheng Li, Dinggang Shen, Tianming Liu, Xiang Li
Text data augmentation is an effective strategy for overcoming the challenge of limited sample sizes in many natural language processing (NLP) tasks.
no code implementations • 21 Feb 2023 • Wenxiong Liao, Zhengliang Liu, Haixing Dai, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Yuzhong Chen, Xi Jiang, Wei Liu, Dajiang Zhu, Tianming Liu, Sheng Li, Xiang Li, Hongmin Cai
The main challenge of FSL is the difficulty of training robust models on small amounts of samples, which frequently leads to overfitting.
no code implementations • 31 Jan 2023 • Xiaowei Yu, Lu Zhang, Haixing Dai, Lin Zhao, Yanjun Lyu, Zihao Wu, Tianming Liu, Dajiang Zhu
To solve this fundamental problem, we design a novel Twin-Transformer framework to unveil the unique functional roles of gyri and sulci as well as their relationship in the whole brain function.
no code implementations • 21 Nov 2022 • Xin Wang, Hong Chen, Si'ao Tang, Zihao Wu, Wenwu Zhu
Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation form.
no code implementations • 5 Nov 2022 • Hongmin Cai, Wenxiong Liao, Zhengliang Liu, Yiyang Zhang, Xiaoke Huang, Siqi Ding, Hui Ren, Zihao Wu, Haixing Dai, Sheng Li, Lingfei Wu, Ninghao Liu, Quanzheng Li, Tianming Liu, Xiang Li
In this framework, we apply distant-supervision on cross-domain knowledge graph adaptation.
no code implementations • 26 Oct 2022 • Zihao Wu, Huy Tran, Hamed Pirsiavash, Soheil Kolouri
Moreover, it is imaginable that when learning from multiple tasks, a small subset of these tasks could behave as adversarial tasks reducing the overall learning performance in a multi-task setting.
no code implementations • 22 Jun 2022 • Lin Zhao, Haixing Dai, Zihao Wu, Zhenxiang Xiao, Lu Zhang, David Weizhong Liu, Xintao Hu, Xi Jiang, Sheng Li, Dajiang Zhu, Tianming Liu
However, whether there exists semantic correlations/connections between the visual representations in ANNs and those in BNNs remains largely unexplored due to both the lack of an effective tool to link and couple two different domains, and the lack of a general and effective framework of representing the visual semantics in BNNs such as human functional brain networks (FBNs).
no code implementations • 25 May 2022 • Chong Ma, Lin Zhao, Yuzhong Chen, Lu Zhang, Zhenxiang Xiao, Haixing Dai, David Liu, Zihao Wu, Zhengliang Liu, Sheng Wang, Jiaxing Gao, Changhe Li, Xi Jiang, Tuo Zhang, Qian Wang, Dinggang Shen, Dajiang Zhu, Tianming Liu
To address this problem, we propose to infuse human experts' intelligence and domain knowledge into the training of deep neural networks.
no code implementations • 20 May 2022 • Yuzhong Chen, Zhenxiang Xiao, Lin Zhao, Lu Zhang, Haixing Dai, David Weizhong Liu, Zihao Wu, Changhe Li, Tuo Zhang, Changying Li, Dajiang Zhu, Tianming Liu, Xi Jiang
However, for data-intensive models such as vision transformer (ViT), current fine-tuning based FSL approaches are inefficient in knowledge generalization and thus degenerate the downstream task performances.
no code implementations • Elsevier Applied Energy 2020 • Peng Kou, Deliang Liang, Chen Wang, Zihao Wu, Lin Gaoa
In this scheme, the optimal voltage control problem is formulated as a constrained Markov decision process, in which both state and action spaces are continuous.
1 code implementation • 13 Nov 2019 • Samuel W. Remedios, Zihao Wu, Camilo Bermudez, Cailey I. Kerley, Snehashis Roy, Mayur B. Patel, John A. Butman, Bennett A. Landman, Dzung L. Pham
Multiple instance learning (MIL) is a supervised learning methodology that aims to allow models to learn instance class labels from bag class labels, where a bag is defined to contain multiple instances.