1 code implementation • 26 Mar 2024 • Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang
Attempting to complement this deficiency, we investigate layerwise properties of LoRA on fine-tuning tasks and observe an uncommon skewness of weight norms across different layers.
no code implementations • 20 Feb 2024 • YuHang Zhou, Yuchen Ni, Xiang Liu, Jian Zhang, Sen Liu, Guangnan Ye, Hongfeng Chai
Large Language Models (LLMs) are progressively being adopted in financial analysis to harness their extensive knowledge base for interpreting complex market data and trends.
no code implementations • 3 Feb 2024 • Peijie Dong, Lujun Li, Xinglin Pan, Zimian Wei, Xiang Liu, Qiang Wang, Xiaowen Chu
Recent advancements in Zero-shot Neural Architecture Search (NAS) highlight the efficacy of zero-cost proxies in various NAS benchmarks.
no code implementations • 23 Jan 2024 • Xiang Liu, Jiahong Chen, Bin Chen, Zimo Liu, Baoyi An, Shu-Tao Xia
With different parameter settings, our method can outperform popular AE-based codecs in constrained environments in terms of both quality and decoding time, or achieve state-of-the-art reconstruction quality compared to other INR codecs.
1 code implementation • 12 Jan 2024 • Shuaijie She, Wei Zou, ShuJian Huang, Wenhao Zhu, Xiang Liu, Xiang Geng, Jiajun Chen
To enhance reasoning abilities in non-dominant languages, we propose a Multilingual-Alignment-as-Preference Optimization framework (MAPO), aiming to align the reasoning processes in other languages with the dominant language.
1 code implementation • 14 Nov 2023 • Rui Pan, Shuo Xing, Shizhe Diao, Wenhe Sun, Xiang Liu, Kashun Shum, Renjie Pi, Jipeng Zhang, Tong Zhang
Since the emergence of large language models, prompt learning has become a popular method for optimizing and customizing these models.
no code implementations • 7 Nov 2023 • Longteng Zhang, Xiang Liu, Zeyu Li, Xinglin Pan, Peijie Dong, Ruibo Fan, Rui Guo, Xin Wang, Qiong Luo, Shaohuai Shi, Xiaowen Chu
For end users, our benchmark and findings help better understand different optimization techniques, training and inference frameworks, together with hardware platforms in choosing configurations for deploying LLMs.
no code implementations • 30 Sep 2023 • Xiang Liu, Liangxi Liu, Feiyang Ye, Yunheng Shen, Xia Li, Linshan Jiang, Jialin Li
Efficiently aggregating trained neural networks from local clients into a global model on a server is a widely researched topic in federated learning.
1 code implementation • 23 Jun 2023 • Cong Shen, Xiang Liu, Jiawei Luo, Kelin Xia
This demonstrates that analytic torsion is a highly efficient topological invariant in the characterization of graph structures and can significantly boost the performance of GNNs.
no code implementations • 6 Mar 2023 • Wenli Zhang, Jiaheng Xie, Zhu Zhang, Xiang Liu
Depression is a common disease worldwide.
no code implementations • 20 Jan 2023 • Luyao Chen, Zhiqiang Chen, Longsheng Jiang, Xiang Liu, Linlu Xu, Bo Zhang, Xiaolong Zou, Jinying Gao, Yu Zhu, Xizi Gong, Shan Yu, Sen Song, Liangyi Chen, Fang Fang, Si Wu, Jia Liu
Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation.
no code implementations • 12 Dec 2022 • Yufei Xie, Xiang Liu, Qizhong Yuan
Based on the practical process of innovation and entrepreneurship education for college students in the author's university, this study analyzes and deconstructs the key concepts of AI knowledge-based crowdsourcing on the basis of literature research, and analyzes the objective fitting needs of combining AI knowledge-based crowdsourcing with college students' innovation and entrepreneurship education practice through a survey and research of a random sample of college students, and verifies that college students' knowledge and application of AI knowledge-based crowdsourcing in the learning and practice of innovation and entrepreneurship The study also verifies the awareness and application of AI knowledge-based crowdsourcing knowledge by university students in the learning and practice of innovation and entrepreneurship.
no code implementations • ECCV 2022 • Kongzhu Jiang, Tianzhu Zhang, Xiang Liu, Bingqiao Qian, Yongdong Zhang, Feng Wu ;
To alleviate the above issues, we propose a novel Cross-Modality Transformer (CMT) to jointly explore a modality-level alignment module and an instance-level module for VI-ReID.
no code implementations • 8 Nov 2022 • Jiaheng Xie, Xiaohang Zhao, Xiang Liu, Xiao Fang
To connect human expertise in the decision-making, safeguard trust for this high-stake prediction, and ensure algorithm transparency, we develop an interpretable deep learning model: Temporal Prototype Network (TempPNet).
no code implementations • 30 Aug 2022 • Xiang Liu, Hongyuan Wang, Zhiqiang Yan, Yu Chen, Xinlong Chen, WeiChun Chen
In this way, the background interference to foreground spacecraft depth completion is effectively avoided.
no code implementations • 1 Jun 2022 • Jie Shi, Chenfei Wu, Jian Liang, Xiang Liu, Nan Duan
Our work proposes a VQ-VAE architecture model with a diffusion decoder (DiVAE) to work as the reconstructing component in image synthesis.
no code implementations • 2 Sep 2021 • Xiang Liu, Tianyao Huang, Yimin Liu
With this constraint, we formulate and solve the signal-to-interference-plus-noise ratio (SINR) balancing problem for multiuser transmit beamforming via convex optimization.
no code implementations • CVPR 2021 • Yulin Li, Jianfeng He, Tianzhu Zhang, Xiang Liu, Yongdong Zhang, Feng Wu
To address these issues, we propose a novel end-to-end Part-Aware Transformer (PAT) for occluded person Re-ID through diverse part discovery via a transformer encoderdecoder architecture, including a pixel context based transformer encoder and a part prototype based transformer decoder.
no code implementations • 4 Mar 2021 • Xin-Dian Yang, Fu-Lai Wang, Zhan-Wei Liu, Xiang Liu
Very recently, the LHCb Collaboration at the Large Hadron Collider at CERN observed new resonance $X(4630)$.
High Energy Physics - Phenomenology
no code implementations • 27 Jan 2021 • Fu-Lai Wang, Xin-Dian Yang, Rui Chen, Xiang Liu
Our results suggest that the $\Omega_{c}\bar D_s^*$ state with $J^P={3}/{2}^{-}$ and the $\Omega_{c}^{*}\bar D_s^*$ state with $J^P={5}/{2}^{-}$ can be recommended as the candidates of the hidden-charm molecular pentaquark with triple strangeness.
High Energy Physics - Phenomenology High Energy Physics - Experiment
no code implementations • 26 Jan 2021 • Bing Chen, Si-Qiang Luo, Xiang Liu
The mass gaps existing in the discovered single heavy flavor baryons are analyzed, which show some universal behaviors.
High Energy Physics - Phenomenology
no code implementations • 11 Jan 2021 • Xuewen Zhang, Yan Qin, Chau Yuen, Lahiru Jayasinghe, Xiang Liu
Out of this consideration, an enhanced RUL framework focusing on data self-generation is put forward for both non-cyclic and cyclic degradation patterns for the first time.
no code implementations • 22 Dec 2020 • Xiang Liu, Deborah Cohen, Tianyao Huang, Yimin Liu, Yonina C. Eldar
Our method encodes each pulse with a random phase, varying from pulse to pulse, and then processes the received samples jointly to resolve the range ambiguity.
1 code implementation • 24 Nov 2020 • Hongyuan Wang, Xiang Liu, Wen Kang, Zhiqiang Yan, Bingwen Wang, Qianhao Ning
In the correspondences credibility computation module, based on the conflicted relationship between the features matching matrix and the coordinates matching matrix, we score the reliability for each correspondence, which can reduce the impact of mismatched or non-matched points.
no code implementations • 2 Nov 2020 • Hua-Xing Chen, Wei Chen, Xiang Liu, Xiao-Hai Liu
We study the $P_{cs}(4459)^0$ recently observed by LHCb using the method of QCD sum rules.
High Energy Physics - Phenomenology High Energy Physics - Experiment
no code implementations • 14 Aug 2020 • Jie Fang, Jian-Wu Lin, Shu-Tao Xia, Yong Jiang, Zhikang Xia, Xiang Liu
This paper proposes Neural Network-based Automatic Factor Construction (NNAFC), a tailored neural network framework that can automatically construct diversified financial factors based on financial domain knowledge and a variety of neural network structures.
no code implementations • 6 Aug 2020 • Qianru Zhang, Meng Zhang, Chinthaka Gamanayake, Chau Yuen, Zehao Geng, Hirunima Jayasekara, Xuewen Zhang, Chia-wei Woo, Jenny Low, Xiang Liu
With some advanced algorithms, the new technologies are expected to control the production quality based on the digital images.
no code implementations • 9 Feb 2020 • Shenlan Liu, Xiang Liu, Gao Huang, Lin Feng, Lianyu Hu, Dong Jiang, Aibin Zhang, Yang Liu, Hong Qiao
To promote the research on action recognition from competitive sports video clips, we introduce a Figure Skating Dataset (FSD-10) for finegrained sports content analysis.
no code implementations • 22 Jan 2020 • Ziyang Tang, Xiang Liu, Guangyu Shen, Baijian Yang
Aerial imagery has been increasingly adopted in mission-critical tasks, such as traffic surveillance, smart cities, and disaster assistance.
no code implementations • 26 Dec 2019 • Jie Fang, Shu-Tao Xia, Jian-Wu Lin, Zhikang Xia, Xiang Liu, Yong Jiang
This paper proposes Alpha Discovery Neural Network (ADNN), a tailored neural network structure which can automatically construct diversified financial technical indicators based on prior knowledge.
no code implementations • 3 Mar 2019 • Xiang Liu, Ziyang Tang, Huyunting Huang, Tonglin Zhang, Baijian Yang
Results showed our approaches can achieve closed-form solutions of multiple models at the cost of half training time of the traditional methods for a single model.
1 code implementation • 11 Jan 2019 • Shenglan Liu, Dong Jiang, Lin Feng, Feilong Wang, Zhanbo Feng, Xiang Liu, Shuai Guo, Bingjun Li, Yuchen Cong
We finally design a Rubik's cube robot and construct a dataset to illustrate the efficiency and effectiveness of our online methods and to indicate the ineffectiveness of offline method by color drifting in our dataset.
1 code implementation • 5 Nov 2018 • Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze
This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.
no code implementations • 25 Oct 2018 • Shenglan Liu, Xiang Liu, Yang Liu, Lin Feng, Hong Qiao, Jian Zhou, Yang Wang
Supervised learning methods are widely used in machine learning.
1 code implementation • 11 Nov 2017 • Wenting Ye, Xiang Liu, Tianwei Yue, Wenping Wang
We proposed the sparse graph-structured linear mixed model (sGLMM) that can incorporate the relatedness information from traits in a dataset with confounding correction.
no code implementations • 7 May 2017 • Dong Wu, Xiang Liu, Feng Xue, Hanqing Zheng, Yehang Shou, Wen Jiang
In this paper, a new decision making methodology based on Z-numbers is presented.