1 code implementation • 28 Dec 2024 • Miao Yu, Junfeng Fang, Yingjie Zhou, Xing Fan, Kun Wang, Shirui Pan, Qingsong Wen
While safety-aligned large language models (LLMs) are increasingly used as the cornerstone for powerful systems such as multi-agent frameworks to solve complex real-world problems, they still suffer from potential adversarial queries, such as jailbreak attacks, which attempt to induce harmful content.
no code implementations • 21 Nov 2024 • Lan Jiang, Yuchao Zheng, Miao Yu, Haiqing Zhang, Fatemah Aladwani, Alessandro Perelli
Accurate brain tumor segmentation remains a challenging task due to structural complexity and great individual differences of gliomas.
no code implementations • 21 Oct 2024 • Miao Yu, Shilong Wang, Guibin Zhang, Junyuan Mao, Chenlong Yin, Qijiong Liu, Qingsong Wen, Kun Wang, Yang Wang
Large language models (LLMs) have empowered nodes within multi-agent networks with intelligence, showing growing applications in both academia and industry.
no code implementations • 15 Oct 2024 • Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng
Recent advancements in large language model (LLM)-based agents have demonstrated that collective intelligence can significantly surpass the capabilities of individual agents, primarily due to well-crafted inter-agent communication topologies.
1 code implementation • 2 Oct 2024 • Miao Yu, Junyuan Mao, Guibin Zhang, Jingheng Ye, Junfeng Fang, Aoxiao Zhong, Yang Liu, Yuxuan Liang, Kun Wang, Qingsong Wen
Research into the external behaviors and internal mechanisms of large language models (LLMs) has shown promise in addressing complex tasks in the physical world.
no code implementations • 1 Oct 2024 • Amirhossein Yazdkhasti, Sophie Lloyd, Joseph H. Schwab, Miao Yu, Hamid Ghaednia
We are introducing a new approachin interpreting ultrasonic signals and we prove in a finite element environment that our method can be used to assess replacement condition.
no code implementations • 11 Sep 2024 • Hitesh Kyatham, Shahriar Negahdaripour, Michael Xu, Xiaomin Lin, Miao Yu, Yiannis Aloimonos
Various local feature detectors developed for RGB images are not well-suited for sonar data.
no code implementations • 15 Sep 2023 • Zixuan Li, Haiying Lin, Zhangyu Wang, Huazhi Li, Miao Yu, Jie Wang
Unstructured road scenes represented by open-pit mines have irregular boundary lines and uneven road surfaces, which lead to segmentation errors in current ground segmentation methods.
1 code implementation • 26 Oct 2022 • Xiaomin Lin, Cheng Liu, Allen Pattillo, Miao Yu, Yiannis Aloimonous
To this end, we present a new benchmark suite, SeaDroneSim, that can be used to create photo-realistic aerial image datasets with the ground truth for segmentation masks of any given object.
no code implementations • 20 Apr 2022 • Miao Yu, Tingting Xiang, Venkata Pavan Kumar Miriyala, Trevor E. Carlson
Machine learning, particularly deep neural network inference, has become a vital workload for many computing systems, from data centers and HPC systems to edge-based computing.
no code implementations • 15 Oct 2020 • Wenchi Ma, Miao Yu, Kaidong Li, Guanghui Wang
This paper, for the first time, reveals the fundamental reason that impedes the scale-up of layer-wise learning is due to the relatively poor separability of the feature space in shallow layers.
2 code implementations • CVPR 2019 • Zhen Zhu, Tengteng Huang, Baoguang Shi, Miao Yu, Bofei Wang, Xiang Bai
This paper proposes a new generative adversarial network for pose transfer, i. e., transferring the pose of a given person to a target pose.
Ranked #1 on
Pose Transfer
on Market-1501
6 code implementations • 13 Jan 2019 • Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivantik, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yu, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.
no code implementations • 18 Feb 2017 • Chunlei Li, Guangshuai Gao, Zhoufeng Liu, Di Huang, Sheng Liu, Miao Yu
In order to accurately detect defects in patterned fabric images, a novel detection algorithm based on Gabor-HOG (GHOG) and low-rank decomposition is proposed in this paper.
no code implementations • 1 Dec 2015 • Miao Yu, Shuhan Shen, Zhanyi Hu
Through both the splitting and merging, we further propose a dynamic parallel and distributed graph-cuts algorithm with guaranteed convergence to the globally optimal solutions within a predefined number of iterations.