2 code implementations • COLING (TextGraphs) 2020 • Weibin Li, Yuxiang Lu, Zhengjie Huang, Weiyue Su, Jiaxiang Liu, Shikun Feng, Yu Sun
To address this problem, we use a pre-trained language model to recall the top-K relevant explanations for each question.
no code implementations • Findings (EMNLP) 2021 • Zujun Dou, Yu Hong, Yu Sun, Guodong Zhou
Training implicit discourse relation classifiers suffers from data sparsity.
no code implementations • ICML 2020 • Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei Efros, University of California Moritz Hardt
We introduce a general approach, called test-time training, for improving the performance of predictive models when training and test data come from different distributions.
no code implementations • 10 Apr 2025 • Xinyang Zhou, Yongyong Ren, Qianqian Zhao, Daoyi Huang, Xinbo Wang, Tingting Zhao, Zhixing Zhu, Wenyuan He, Shuyuan Li, Yan Xu, Yu Sun, Yongguo Yu, Shengnan Wu, Jian Wang, Guangjun Yu, Dake He, Bo Ban, Hui Lu
Accurate diagnosis of Mendelian diseases is crucial for precision therapy and assistance in preimplantation genetic diagnosis.
no code implementations • 7 Apr 2025 • Karan Dalal, Daniel Koceja, Gashon Hussein, Jiarui Xu, Yue Zhao, Youjin Song, Shihao Han, Ka Chun Cheung, Jan Kautz, Carlos Guestrin, Tatsunori Hashimoto, Sanmi Koyejo, Yejin Choi, Yu Sun, Xiaolong Wang
We have only experimented with one-minute videos due to resource constraints, but the approach can be extended to longer videos and more complex stories.
no code implementations • 21 Mar 2025 • Yu Sun, Yin Li, Ruixiao Sun, Chunhui Liu, Fangming Zhou, Ze Jin, Linjie Wang, Xiang Shen, Zhuolin Hao, Hongyu Xiong
Transformer-based multimodal models are widely used in industrial-scale recommendation, search, and advertising systems for content understanding and relevance ranking.
no code implementations • 14 Mar 2025 • Hongkai Zheng, Wenda Chu, Bingliang Zhang, Zihui Wu, Austin Wang, Berthy T. Feng, Caifeng Zou, Yu Sun, Nikola Kovachki, Zachary E. Ross, Katherine L. Bouman, Yisong Yue
Plug-and-play diffusion priors (PnPDP) have emerged as a promising research direction for solving inverse problems.
no code implementations • 8 Mar 2025 • Md Sadman Sakib, Yu Sun
To address this, we propose STAR (Smart Task Adaptation and Recovery), a novel framework that synergizes Foundation Models (FMs) with dynamically expanding Knowledge Graphs (KGs) to enable resilient task planning and autonomous failure recovery.
no code implementations • 6 Mar 2025 • Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi, Ahmed Elbakary, Alexandros Nikou, Ali Maatouk, Ali Mokh, Amirreza Kazemi, Antonio De Domenico, Athanasios Karapantelakis, Bo Cheng, Bo Yang, Bohao Wang, Carlo Fischione, Chao Zhang, Chaouki Ben Issaid, Chau Yuen, Chenghui Peng, Chongwen Huang, Christina Chaccour, Christo Kurisummoottil Thomas, Dheeraj Sharma, Dimitris Kalogiros, Dusit Niyato, Eli de Poorter, Elissa Mhanna, Emilio Calvanese Strinati, Faouzi Bader, Fathi Abdeldayem, Fei Wang, Fenghao Zhu, Gianluca Fontanesi, Giovanni Geraci, Haibo Zhou, Hakimeh Purmehdi, Hamed Ahmadi, Hang Zou, Hongyang Du, Hoon Lee, Howard H. Yang, Iacopo Poli, Igor Carron, Ilias Chatzistefanidis, Inkyu Lee, Ioannis Pitsiorlas, Jaron Fontaine, Jiajun Wu, Jie Zeng, Jinan Li, Jinane Karam, Johny Gemayel, Juan Deng, Julien Frison, Kaibin Huang, Kehai Qiu, Keith Ball, Kezhi Wang, Kun Guo, Leandros Tassiulas, Lecorve Gwenole, Liexiang Yue, Lina Bariah, Louis Powell, Marcin Dryjanski, Maria Amparo Canaveras Galdon, Marios Kountouris, Maryam Hafeez, Maxime Elkael, Mehdi Bennis, Mehdi Boudjelli, Meiling Dai, Merouane Debbah, Michele Polese, Mohamad Assaad, Mohamed Benzaghta, Mohammad Al Refai, Moussab Djerrab, Mubeen Syed, Muhammad Amir, Na Yan, Najla Alkaabi, Nan Li, Nassim Sehad, Navid Nikaein, Omar Hashash, Pawel Sroka, Qianqian Yang, Qiyang Zhao, Rasoul Nikbakht Silab, Rex Ying, Roberto Morabito, Rongpeng Li, Ryad Madi, Salah Eddine El Ayoubi, Salvatore D'Oro, Samson Lasaulce, Serveh Shalmashi, Sige Liu, Sihem Cherrared, Swarna Bindu Chetty, Swastika Dutta, Syed A. R. Zaidi, Tianjiao Chen, Timothy Murphy, Tommaso Melodia, Tony Q. S. Quek, Vishnu Ram, Walid Saad, Wassim Hamidouche, Weilong Chen, Xiaoou Liu, Xiaoxue Yu, Xijun Wang, Xingyu Shang, Xinquan Wang, Xuelin Cao, Yang Su, Yanping Liang, Yansha Deng, Yifan Yang, Yingping Cui, Yu Sun, Yuxuan Chen, Yvan Pointurier, Zeinab Nehme, Zeinab Nezami, Zhaohui Yang, Zhaoyang Zhang, Zhe Liu, Zhenyu Yang, Zhu Han, Zhuang Zhou, Zihan Chen, Zirui Chen, Zitao Shuai
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions and user experiences, especially in the context of 6G systems.
no code implementations • 3 Mar 2025 • Jianzhe Xue, Dongcheng Yuan, Zhanxi Ma, Tiankai Jiang, Yu Sun, Haibo Zhou, Xuemin Shen
Channel prediction is crucial for high-mobility vehicular networks, as it enables the anticipation of future channel conditions and the proactive adjustment of communication strategies.
no code implementations • 19 Feb 2025 • Naibin Gu, Zhenyu Zhang, Xiyu Liu, Peng Fu, Zheng Lin, Shuohuan Wang, Yu Sun, Hua Wu, Weiping Wang, Haifeng Wang
Due to the demand for efficient fine-tuning of large language models, Low-Rank Adaptation (LoRA) has been widely adopted as one of the most effective parameter-efficient fine-tuning methods.
no code implementations • 19 Feb 2025 • Yilong Chen, Junyuan Shang, Zhenyu Zhang, Yanxi Xie, Jiawei Sheng, Tingwen Liu, Shuohuan Wang, Yu Sun, Hua Wu, Haifeng Wang
Large language models (LLMs) face inherent performance bottlenecks under parameter constraints, particularly in processing critical tokens that demand complex reasoning.
no code implementations • 5 Feb 2025 • Wang Xinyi, Kang Hongyu, Wei Peishan, Shuai Li, Yu Sun, Sai Kit Lam, Yongping Zheng
In this paper, we aim to address the unmet demand for automated prompting and enhanced human-model interactions of SAM and SAM2 for the sake of promoting their widespread clinical adoption.
1 code implementation • 20 Jan 2025 • Haoran Sun, Yekun Chai, Shuohuan Wang, Yu Sun, Hua Wu, Haifeng Wang
Reinforcement learning from human feedback (RLHF) has proven effective in aligning large language models (LLMs) with human preferences, but often at the cost of reduced output diversity.
no code implementations • 15 Jan 2025 • Kangli Dong, Siya Chen, Ying Dan, Lu Zhang, Xinyi Li, Wei Liang, Yue Zhao, Yu Sun
Results show that the energy associated with optimal stochastic tracking control is negatively correlated with the intrinsic average controllability of the brain network system, while the energy of the optimal state approaching control is significantly related to the target state value.
1 code implementation • 24 Dec 2024 • Xinyu Yang, Yu Sun, Xinyang Chen, Ying Zhang, Xiaojie Yuan
Spatial-temporal data collected across different geographic locations often suffer from missing values, posing challenges to data analysis.
no code implementations • 10 Dec 2024 • Zachary Coalson, Jeonghyun Woo, Shiyang Chen, Yu Sun, Lishan Yang, Prashant Nair, Bo Fang, Sanghyun Hong
We show that our attack can reliably induce jailbreaking in systems similar to those affected by prior bit-flip attacks.
no code implementations • 7 Dec 2024 • Yilong Chen, Junyuan Shang, Zhengyu Zhang, Jiawei Sheng, Tingwen Liu, Shuohuan Wang, Yu Sun, Hua Wu, Haifeng Wang
MOHD offers a new perspective for scaling the model, showcasing the potential of hidden dimension sparsity to boost efficiency
no code implementations • 1 Dec 2024 • Yu Zhang, Shuang Li, Yibing Wang, Yu Sun, Wenyi Xiang
The shape prior is a probability matrix derived from the reconstruction results of multiple sets of random partial array signals in a computational imaging system using any reconstruction algorithm, such as Delay-and-Sum (DAS) and Back-Projection (BP).
no code implementations • 15 Nov 2024 • Jingru Yang, Huan Yu, Yang Jingxin, Chentianye Xu, Yin Biao, Yu Sun, Shengfeng He
The Linguistic Agent evaluates and refines detections by reasoning over spatial and contextual relationships among objects, while the classification Vision Agent offers corrective feedback to improve classification accuracy.
1 code implementation • 3 Oct 2024 • Yekun Chai, Haoran Sun, Huang Fang, Shuohuan Wang, Yu Sun, Hua Wu
However, token-level RLHF suffers from the credit assignment problem over long sequences, where delayed rewards make it challenging for the model to discern which actions contributed to successful outcomes.
no code implementations • 2 Oct 2024 • Tingfeng Hui, Zhenyu Zhang, Shuohuan Wang, Yu Sun, Hua Wu, Sen Su
To ensure that each specialized expert in the MoE model works as expected, we select a small amount of seed data that each expert excels to pre-optimize the router.
no code implementations • 23 Sep 2024 • Chenxu Yang, Ruipeng Jia, Naibin Gu, Zheng Lin, Siyuan Chen, Chao Pang, Weichong Yin, Yu Sun, Hua Wu, Weiping Wang
Hence, we introduce orthogonal finetuning for DPO via a weight-Rotated Preference Optimization (RoPO) method, which merely conducts rotational and magnitude-stretching updates on the weight parameters to maintain the hyperspherical energy invariant, thereby preserving the knowledge encoded in the angle between neurons.
no code implementations • 27 Aug 2024 • Haojun Jiang, Zhenguo Sun, Yu Sun, Ning Jia, Meng Li, Shaqi Luo, Shiji Song, Gao Huang
Specifically, our approach learns personalized 2D and 3D cardiac structural features by predicting the masked-out images and actions in a scanning sequence.
2 code implementations • 7 Aug 2024 • Yilong Chen, Guoxia Wang, Junyuan Shang, Shiyao Cui, Zhenyu Zhang, Tingwen Liu, Shuohuan Wang, Yu Sun, dianhai yu, Hua Wu
Large Language Models (LLMs) have ignited an innovative surge of AI applications, marking a new era of exciting possibilities equipped with extended context windows.
no code implementations • 31 Jul 2024 • Wenyuan Chen, Haocong Song, Changsheng Dai, Aojun Jiang, Guanqiao Shan, Hang Liu, Yanlong Zhou, Khaled Abdalla, Shivani N Dhanani, Katy Fatemeh Moosavi, Shruti Pathak, Clifford Librach, Zhuoran Zhang, Yu Sun
Automated morphology analysis of a high number of sperm requires accurate segmentation of each sperm part and quantitative morphology evaluation.
no code implementations • 10 Jul 2024 • Jianzhe Xue, Dongcheng Yuan, Yu Sun, Tianqi Zhang, Wenchao Xu, Haibo Zhou, Xuemin, Shen
The growing number of connected vehicles offers an opportunity to leverage internet of vehicles (IoV) data for traffic state estimation (TSE) which plays a crucial role in intelligent transportation systems (ITS).
3 code implementations • 5 Jul 2024 • Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin
We evaluate our instantiations at the scale of 125M to 1. 3B parameters, comparing with a strong Transformer and Mamba, a modern RNN.
no code implementations • 28 Jun 2024 • Haojun Jiang, Meng Li, Zhenguo Sun, Ning Jia, Yu Sun, Shaqi Luo, Shiji Song, Gao Huang
The complex structure of the heart leads to significant challenges in echocardiography, especially in acquisition cardiac ultrasound images.
no code implementations • 19 Jun 2024 • Haojun Jiang, Zhenguo Sun, Ning Jia, Meng Li, Yu Sun, Shaqi Luo, Shiji Song, Gao Huang
However, there is a severe shortage of experienced cardiac sonographers, due to the heart's complex structure and significant operational challenges.
no code implementations • 3 Jun 2024 • Yilong Chen, Linhao Zhang, Junyuan Shang, Zhenyu Zhang, Tingwen Liu, Shuohuan Wang, Yu Sun
Large language models (LLMs) with billions of parameters demonstrate impressive performance.
1 code implementation • 29 May 2024 • Zihui Wu, Yu Sun, Yifan Chen, Bingliang Zhang, Yisong Yue, Katherine L. Bouman
Diffusion models (DMs) have recently shown outstanding capabilities in modeling complex image distributions, making them expressive image priors for solving Bayesian inverse problems.
no code implementations • 19 May 2024 • Gengchen Wei, Xinle Pang, Tianning Zhang, Yu Sun, Xun Qian, Chen Lin, Han-sen Zhong, Wanli Ouyang
With over 200 million published academic documents and millions of new documents being written each year, academic researchers face the challenge of searching for information within this vast corpus.
no code implementations • 29 Apr 2024 • Tingfeng Hui, Zhenyu Zhang, Shuohuan Wang, Weiran Xu, Yu Sun, Hua Wu
Large language models (LLMs) with one or more fine-tuning phases have become a necessary step to unlock various capabilities, enabling LLMs to follow natural language instructions or align with human preferences.
1 code implementation • CVPR 2024 • Sai Kumar Dwivedi, Yu Sun, Priyanka Patel, Yao Feng, Michael J. Black
We address the problem of regressing 3D human pose and shape from a single image, with a focus on 3D accuracy.
Ranked #35 on
3D Human Pose Estimation
on 3DPW
1 code implementation • 16 Apr 2024 • Yekun Chai, Qingyi Liu, Jingwu Xiao, Shuohuan Wang, Yu Sun, Hua Wu
Our extensive evaluation across a wide range of benchmarks shows that incorporating both visual and textual data significantly improves the performance of pixel-based language models.
2 code implementations • 11 Apr 2024 • Yekun Chai, Qingyi Liu, Shuohuan Wang, Yu Sun, Qiwei Peng, Hua Wu
This paper presents GPTfluence, a novel approach that leverages a featurized simulation to assess the impact of training examples on the training dynamics of GPT models.
no code implementations • 9 Apr 2024 • Francis Tsow, Tianze Chen, Yu Sun
A robot performing multi-object grasping needs to sense the number of objects in the hand after grasping.
3 code implementations • 26 Mar 2024 • Zheng Cai, Maosong Cao, Haojiong Chen, Kai Chen, Keyu Chen, Xin Chen, Xun Chen, Zehui Chen, Zhi Chen, Pei Chu, Xiaoyi Dong, Haodong Duan, Qi Fan, Zhaoye Fei, Yang Gao, Jiaye Ge, Chenya Gu, Yuzhe Gu, Tao Gui, Aijia Guo, Qipeng Guo, Conghui He, Yingfan Hu, Ting Huang, Tao Jiang, Penglong Jiao, Zhenjiang Jin, Zhikai Lei, Jiaxing Li, Jingwen Li, Linyang Li, Shuaibin Li, Wei Li, Yining Li, Hongwei Liu, Jiangning Liu, Jiawei Hong, Kaiwen Liu, Kuikun Liu, Xiaoran Liu, Chengqi Lv, Haijun Lv, Kai Lv, Li Ma, Runyuan Ma, Zerun Ma, Wenchang Ning, Linke Ouyang, Jiantao Qiu, Yuan Qu, FuKai Shang, Yunfan Shao, Demin Song, Zifan Song, Zhihao Sui, Peng Sun, Yu Sun, Huanze Tang, Bin Wang, Guoteng Wang, Jiaqi Wang, Jiayu Wang, Rui Wang, Yudong Wang, Ziyi Wang, Xingjian Wei, Qizhen Weng, Fan Wu, Yingtong Xiong, Chao Xu, Ruiliang Xu, Hang Yan, Yirong Yan, Xiaogui Yang, Haochen Ye, Huaiyuan Ying, JIA YU, Jing Yu, Yuhang Zang, Chuyu Zhang, Li Zhang, Pan Zhang, Peng Zhang, Ruijie Zhang, Shuo Zhang, Songyang Zhang, Wenjian Zhang, Wenwei Zhang, Xingcheng Zhang, Xinyue Zhang, Hui Zhao, Qian Zhao, Xiaomeng Zhao, Fengzhe Zhou, Zaida Zhou, Jingming Zhuo, Yicheng Zou, Xipeng Qiu, Yu Qiao, Dahua Lin
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
no code implementations • 4 Mar 2024 • Yu Sun, Dongzhan Zhou, Chen Lin, Conghui He, Wanli Ouyang, Han-sen Zhong
Academic documents are packed with texts, equations, tables, and figures, requiring comprehensive understanding for accurate Optical Character Recognition (OCR).
2 code implementations • 26 Jan 2024 • Yu Sun, Keyu Chen, Shujie Wang, Peiji Li, Qipeng Guo, Hang Yan, Xipeng Qiu, Xuanjing Huang, Dahua Lin
However, these evaluation benchmarks are limited to assessing the instruction-following capabilities, overlooking the fundamental abilities that emerge during the pre-training stage.
1 code implementation • 22 Jan 2024 • Yu Sun, Gaojian Xiong, Xianxun Yao, Kailang Ma, Jian Cui
Deep gradient inversion attacks expose a serious threat to Federated Learning (FL) by accurately recovering private data from shared gradients.
no code implementations • 15 Jan 2024 • Md Sadman Sakib, Yu Sun
Leveraging GPT-4 further, the high-level task plan is converted into a low-level Planning Domain Definition Language (PDDL) plan executable by a robot.
1 code implementation • 1 Dec 2023 • Kai Lv, Shuo Zhang, Tianle Gu, Shuhao Xing, Jiawei Hong, Keyu Chen, Xiaoran Liu, Yuqing Yang, Honglin Guo, Tengxiao Liu, Yu Sun, Qipeng Guo, Hang Yan, Xipeng Qiu
This paper introduces CoLLiE, an efficient library that facilitates collaborative training of large language models using 3D parallelism, parameter-efficient fine-tuning (PEFT) methods, and optimizers such as Lion, Adan, Sophia, LOMO and AdaLomo.
no code implementations • CVPR 2024 • Yao Feng, Jing Lin, Sai Kumar Dwivedi, Yu Sun, Priyanka Patel, Michael J. Black
Additionally, ChatPose empowers LLMs to apply their extensive world knowledge in reasoning about human poses, leading to two advanced tasks: speculative pose generation and reasoning about pose estimation.
1 code implementation • 20 Oct 2023 • Yu Sun, Xinhao Li, Karan Dalal, Chloe Hsu, Sanmi Koyejo, Carlos Guestrin, Xiaolong Wang, Tatsunori Hashimoto, Xinlei Chen
Our inner loop turns out to be equivalent to linear attention when the inner-loop learner is only a linear model, and to self-attention when it is a kernel estimator.
1 code implementation • 16 Oct 2023 • Yu Sun, Zihui Wu, Yifan Chen, Berthy T. Feng, Katherine L. Bouman
PMC is able to incorporate expressive score-based generative priors for high-quality image reconstruction while also performing uncertainty quantification via posterior sampling.
1 code implementation • 2 Oct 2023 • Lei LI, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Ningyu Zhang, Hua Wu
We validate our approach across a wide range of domains, incorporating seven distinct external tools.
no code implementations • 17 Sep 2023 • Md Sadman Sakib, Yu Sun
Task planning for robotic cooking involves generating a sequence of actions for a robot to prepare a meal successfully.
no code implementations • 18 Jul 2023 • Hongwei Zheng, Han Li, Bowen Shi, Wenrui Dai, Botao Wan, Yu Sun, Min Guo, Hongkai Xiong
Recent 2D-to-3D human pose estimation (HPE) utilizes temporal consistency across sequences to alleviate the depth ambiguity problem but ignore the action related prior knowledge hidden in the pose sequence.
no code implementations • 11 Jul 2023 • Renhao Wang, Yu Sun, Arnuv Tandon, Yossi Gandelsman, Xinlei Chen, Alexei A. Efros, Xiaolong Wang
Before making a prediction on each test instance, the model is first trained on the same instance using a self-supervised task such as reconstruction.
3 code implementations • CVPR 2023 • Yu Sun, Qian Bao, Wu Liu, Tao Mei, Michael J. Black
Although the estimation of 3D human pose and shape (HPS) is rapidly progressing, current methods still cannot reliably estimate moving humans in global coordinates, which is critical for many applications.
Ranked #58 on
3D Human Pose Estimation
on 3DPW
2 code implementations • 31 May 2023 • Mingguo He, Zhewei Wei, Shikun Feng, Zhengjie Huang, Weibin Li, Yu Sun, dianhai yu
Furthermore, these methods cannot learn arbitrary valid heterogeneous graph filters within the spectral domain, which have limited expressiveness.
Ranked #6 on
Node Property Prediction
on ogbn-mag
1 code implementation • 29 May 2023 • Moritz Hardt, Yu Sun
Surprisingly, retrieving and training on as few as 20 neighbors, each for only one gradient iteration, drastically improves performance across more than 20 language modeling tasks in the Pile.
Ranked #20 on
Language Modelling
on The Pile
1 code implementation • 25 Apr 2023 • Zihui Wu, Tianwei Yin, Yu Sun, Robert Frost, Andre van der Kouwe, Adrian V. Dalca, Katherine L. Bouman
Traditional CS-MRI methods often separately address measurement subsampling, image reconstruction, and task prediction, resulting in a suboptimal end-to-end performance.
1 code implementation • 21 Feb 2023 • Yuchen Wang, Jinghui Zhang, Zhengjie Huang, Weibin Li, Shikun Feng, Ziheng Ma, Yu Sun, dianhai yu, Fang Dong, Jiahui Jin, Beilun Wang, Junzhou Luo
Then, we combine the group aggregation and the learnable encodings into a Transformer encoder to capture the semantic information.
no code implementations • 15 Feb 2023 • Han Li, Bowen Shi, Wenrui Dai, Hongwei Zheng, Botao Wang, Yu Sun, Min Guo, Chenlin Li, Junni Zou, Hongkai Xiong
There has been a recent surge of interest in introducing transformers to 3D human pose estimation (HPE) due to their powerful capabilities in modeling long-term dependencies.
no code implementations • 9 Feb 2023 • Pengfei Zhu, Chao Pang, Yekun Chai, Lei LI, Shuohuan Wang, Yu Sun, Hao Tian, Hua Wu
In response to this lacuna, this paper introduces a pioneering contribution in the form of a text-to-waveform music generation model, underpinned by the utilization of diffusion models.
1 code implementation • International Conference on Learning Representations 2023 • Kailang Ma, Yu Sun, Jian Cui, Dawei Li, Zhenyu Guan and Jianwei Liu
Furthermore, we demonstrate that our method facilitates the existing gradient inversion attacks by exploiting the recovered labels, with an increase of 6-7 in PSNR on both MNIST and CIFAR100.
1 code implementation • 9 Jan 2023 • Weixin Liu, Xuyi Chen, Jiaxiang Liu, Shikun Feng, Yu Sun, Hao Tian, Hua Wu
Experimental results demonstrate that our method yields a student with much better generalization, significantly outperforms existing baselines, and establishes a new state-of-the-art result on in-domain, out-domain, and low-resource datasets in the setting of task-agnostic distillation.
1 code implementation • ICCV 2023 • Zihao Sun, Yu Sun, Longxing Yang, Shun Lu, Jilin Mei, Wenxiao Zhao, Yu Hu
Neural Architecture Search (NAS) aims to automatically find optimal neural network architectures in an efficient way.
1 code implementation • 13 Dec 2022 • Yekun Chai, Shuohuan Wang, Chao Pang, Yu Sun, Hao Tian, Hua Wu
Extensive results show that ERNIE-Code outperforms previous multilingual LLMs for PL or NL across a wide range of end tasks of code intelligence, including multilingual code-to-text, text-to-code, code-to-code, and text-to-text generation.
no code implementations • SemEval (NAACL) 2022 • Yaqian Han, Yekun Chai, Shuohuan Wang, Yu Sun, Hongyi Huang, Guanghao Chen, Yitong Xu, Yang Yang
Detecting sarcasm and verbal irony from people's subjective statements is crucial to understanding their intended meanings and real sentiments and positions in social scenarios.
no code implementations • SemEval (NAACL) 2022 • Junyuan Shang, Shuohuan Wang, Yu Sun, Yanjun Yu, Yue Zhou, Li Xiang, Guixiu Yang
This paper describes our winning system on SemEval 2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts.
no code implementations • 21 Nov 2022 • Paul Goyes, Edwin Vargas, Claudia Correa, Yu Sun, Ulugbek Kamilov, Brendt Wohlberg, Henry Arguello
Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging.
no code implementations • 9 Nov 2022 • Bin Shan, Yaqian Han, Weichong Yin, Shuohuan Wang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Recent cross-lingual cross-modal works attempt to extend Vision-Language Pre-training (VLP) models to non-English inputs and achieve impressive performance.
Ranked #1 on
Multimodal Machine Translation
on Multi30K
2 code implementations • 7 Nov 2022 • Xiaoran Fan, Chao Pang, Tian Yuan, He Bai, Renjie Zheng, Pengfei Zhu, Shuohuan Wang, Junkun Chen, Zeyu Chen, Liang Huang, Yu Sun, Hua Wu
In this paper, we extend the pretraining method for cross-lingual multi-speaker speech synthesis tasks, including cross-lingual multi-speaker voice cloning and cross-lingual multi-speaker speech editing.
no code implementations • 31 Oct 2022 • Xiaotian Zhang, Hang Yan, Yu Sun, Xipeng Qiu
To adapt BERT to the CSC task, we propose a token-level self-distillation contrastive learning method.
2 code implementations • CVPR 2023 • Zhida Feng, Zhenyu Zhang, Xintong Yu, Yewei Fang, Lanxin Li, Xuyi Chen, Yuxiang Lu, Jiaxiang Liu, Weichong Yin, Shikun Feng, Yu Sun, Li Chen, Hao Tian, Hua Wu, Haifeng Wang
Recent progress in diffusion models has revolutionized the popular technology of text-to-image generation.
Ranked #12 on
Text-to-Image Generation
on MS COCO
no code implementations • 21 Oct 2022 • Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Derivative-free prompt learning has emerged as a lightweight alternative to prompt tuning, which only requires model inference to optimize the prompts.
no code implementations • 18 Oct 2022 • Wenbiao Li, Pan Tang, Zhengfan Wu, Weixue Lu, Minghua Zhang, Zhenlei Tian, Daiting Shi, Yu Sun, Simiu Gu, Dawei Yin
Meanwhile, we introduce sentence-level semantic interaction to design a multi-embedding-based retrieval (MEBR) model, which can generate multiple embeddings to deal with different potential queries by using frequently clicked sentences in web pages.
2 code implementations • 12 Oct 2022 • Qiming Peng, Yinxu Pan, Wenjin Wang, Bin Luo, Zhenyu Zhang, Zhengjie Huang, Teng Hu, Weichong Yin, Yongfeng Chen, Yin Zhang, Shikun Feng, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding.
Ranked #2 on
Semantic entity labeling
on FUNSD
1 code implementation • 30 Sep 2022 • Bin Shan, Weichong Yin, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
They attempt to learn cross-modal representation using contrastive learning on image-text pairs, however, the built inter-modal correlations only rely on a single view for each modality.
Ranked #1 on
Image Retrieval
on AIC-ICC
no code implementations • 18 Sep 2022 • Wenjin Wang, Zhengjie Huang, Bin Luo, Qianglong Chen, Qiming Peng, Yinxu Pan, Weichong Yin, Shikun Feng, Yu Sun, dianhai yu, Yin Zhang
At first, a document graph is proposed to model complex relationships among multi-grained multimodal elements, in which salient visual regions are detected by a cluster-based method.
1 code implementation • 15 Sep 2022 • Yossi Gandelsman, Yu Sun, Xinlei Chen, Alexei A. Efros
Test-time training adapts to a new test distribution on the fly by optimizing a model for each test input using self-supervision.
no code implementations • 2 Sep 2022 • Chuanhang Yan, Yu Sun, Qian Bao, Jinhui Pang, Wu Liu, Tao Mei
We develop WOC, a webcam-based 3D virtual online chatroom for multi-person interaction, which captures the 3D motion of users and drives their individual 3D virtual avatars in real-time.
1 code implementation • 9 Aug 2022 • Hang Yan, Yu Sun, Xiaonan Li, Xipeng Qiu
In this paper, we propose using Convolutional Neural Network (CNN) to model these spatial relations in the score matrix.
Ranked #3 on
Nested Named Entity Recognition
on ACE 2005
no code implementations • 29 May 2022 • Binyan Hu, Yu Sun, A. K. Qin
Combining multiple DA methods, namely multi-DA, for DNN training, provides a way to boost generalisation.
1 code implementation • 19 May 2022 • Yang Xiang, Zhihua Wu, Weibao Gong, Siyu Ding, Xianjie Mo, Yuang Liu, Shuohuan Wang, Peng Liu, Yongshuai Hou, Long Li, Bin Wang, Shaohuai Shi, Yaqian Han, Yue Yu, Ge Li, Yu Sun, Yanjun Ma, dianhai yu
We took natural language processing (NLP) as an example to show how Nebula-I works in different training phases that include: a) pre-training a multilingual language model using two remote clusters; and b) fine-tuning a machine translation model using knowledge distilled from pre-trained models, which run through the most popular paradigm of recent deep learning.
1 code implementation • 13 May 2022 • Huijuan Wang, Siming Dai, Weiyue Su, Hui Zhong, Zeyang Fang, Zhengjie Huang, Shikun Feng, Zeyu Chen, Yu Sun, dianhai yu
Notably, it averagely brings about 10% relative improvement to triplet-based embedding methods on OGBL-WikiKG2 and takes 5%-83% time to achieve comparable results as the state-of-the-art GC-OTE.
no code implementations • 1 Apr 2022 • Jacqueline Hausmann, Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof, Yu Sun
Current face detection algorithms are extremely generalized and can obtain decent accuracy when detecting the adult faces.
no code implementations • 23 Mar 2022 • Yang Liu, Jiaxiang Liu, Li Chen, Yuxiang Lu, Shikun Feng, Zhida Feng, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
We argue that two factors, information bottleneck sensitivity and inconsistency between different attention topologies, could affect the performance of the Sparse Transformer.
1 code implementation • 28 Feb 2022 • Wentao Shangguan, Yu Sun, Weijie Gan, Ulugbek S. Kamilov
This paper considers the problem of temporal video interpolation, where the goal is to synthesize a new video frame given its two neighbors.
Ranked #1 on
Video Frame Interpolation
on Xiph 4k
no code implementations • 4 Jan 2022 • Xu Wang, Huan Zhao, WeiWei Tu, Hao Li, Yu Sun, Xiaochen Bo
Double-strand DNA breaks (DSBs) are a form of DNA damage that can cause abnormal chromosomal rearrangements.
2 code implementations • 31 Dec 2021 • Han Zhang, Weichong Yin, Yewei Fang, Lanxin Li, Boqiang Duan, Zhihua Wu, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
To explore the landscape of large-scale pre-training for bidirectional text-image generation, we train a 10-billion parameter ERNIE-ViLG model on a large-scale dataset of 145 million (Chinese) image-text pairs which achieves state-of-the-art performance for both text-to-image and image-to-text tasks, obtaining an FID of 7. 9 on MS-COCO for text-to-image synthesis and best results on COCO-CN and AIC-ICC for image captioning.
Ranked #41 on
Text-to-Image Generation
on MS COCO
3 code implementations • 23 Dec 2021 • Shuohuan Wang, Yu Sun, Yang Xiang, Zhihua Wu, Siyu Ding, Weibao Gong, Shikun Feng, Junyuan Shang, Yanbin Zhao, Chao Pang, Jiaxiang Liu, Xuyi Chen, Yuxiang Lu, Weixin Liu, Xi Wang, Yangfan Bai, Qiuliang Chen, Li Zhao, Shiyong Li, Peng Sun, dianhai yu, Yanjun Ma, Hao Tian, Hua Wu, Tian Wu, Wei Zeng, Ge Li, Wen Gao, Haifeng Wang
A unified framework named ERNIE 3. 0 was recently proposed for pre-training large-scale knowledge enhanced models and trained a model with 10 billion parameters.
4 code implementations • CVPR 2022 • Yu Sun, Wu Liu, Qian Bao, Yili Fu, Tao Mei, Michael J. Black
To do so, we exploit a 3D body model space that lets BEV infer shapes from infants to adults.
Ranked #1 on
3D Depth Estimation
on Relative Human
(using extra training data)
no code implementations • 4 Dec 2021 • Md. Sadman Sakib, David Paulius, Yu Sun
To address the problem of producing novel and flexible task plans called task trees, we explore how we can derive plans with concepts not originally in the robot's knowledge base.
1 code implementation • 2 Dec 2021 • Weibin Li, Mingkai He, Zhengjie Huang, Xianming Wang, Shikun Feng, Weiyue Su, Yu Sun
In recent years, owing to the outstanding performance in graph representation learning, graph neural network (GNN) techniques have gained considerable interests in many real-world scenarios, such as recommender systems and social networks.
no code implementations • 30 Nov 2021 • Tianze Chen, Adheesh Shenoy, Anzhelika Kolinko, Syed Shah, Yu Sun
To do so, a robot needs to grasp within a pile, sense the number of objects in the grasp before lifting, and predict the number of objects that will remain in the grasp after lifting.
1 code implementation • 27 Nov 2021 • Renhao Liu, Yu Sun, Jiabei Zhu, Lei Tian, Ulugbek Kamilov
The representation in DeCAF is learned directly from the measurements of the test sample by using the IDT forward model, without any ground-truth RI maps.
1 code implementation • 23 Nov 2021 • Han Li, Bowen Shi, Wenrui Dai, Yabo Chen, Botao Wang, Yu Sun, Min Guo, Chenlin Li, Junni Zou, Hongkai Xiong
Recent 2D-to-3D human pose estimation works tend to utilize the graph structure formed by the topology of the human skeleton.
Ranked #47 on
3D Human Pose Estimation
on MPI-INF-3DHP
(AUC metric)
no code implementations • 29 Sep 2021 • Yang Liu, Jiaxiang Liu, Yuxiang Lu, Shikun Feng, Yu Sun, Zhida Feng, Li Chen, Hao Tian, Hua Wu, Haifeng Wang
The first factor is information bottleneck sensitivity, which is caused by the key feature of Sparse Transformer — only a small number of global tokens can attend to all other tokens.
no code implementations • 5 Aug 2021 • Sidharth Srivatsav Sribhashyam, Md Sirajus Salekin, Dmitry Goldgof, Ghada Zamzmi, Mark Last, Yu Sun
The results from the proposed approach are promising with an accuracy of 91. 55% and 91. 67% in prediction and classification tasks respectively.
no code implementations • 3 Aug 2021 • Yu Sun, Joe Falco, Maximo A. Roa, Berk Calli
This paper discusses recent research progress in robotic grasping and manipulation in the light of the latest Robotic Grasping and Manipulation Competitions (RGMCs).
no code implementations • SEMEVAL 2021 • Zhida Feng, Jiji Tang, Jiaxiang Liu, Weichong Yin, Shikun Feng, Yu Sun, Li Chen
This paper describes our system participated in Task 6 of SemEval-2021: the task focuses on multimodal propaganda technique classification and it aims to classify given image and text into 22 classes.
no code implementations • SEMEVAL 2021 • Chao Pang, Xiaoran Fan, Weiyue Su, Xuyi Chen, Shuohuan Wang, Jiaxiang Liu, Xuan Ouyang, Shikun Feng, Yu Sun
This paper describes our system participated in Task 7 of SemEval-2021: Detecting and Rating Humor and Offense.
1 code implementation • 12 Jul 2021 • Weijie Gan, Yu Sun, Cihat Eldeniz, Jiaming Liu, Hongyu An, Ulugbek S. Kamilov
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets.
2 code implementations • 5 Jul 2021 • Yu Sun, Shuohuan Wang, Shikun Feng, Siyu Ding, Chao Pang, Junyuan Shang, Jiaxiang Liu, Xuyi Chen, Yanbin Zhao, Yuxiang Lu, Weixin Liu, Zhihua Wu, Weibao Gong, Jianzhong Liang, Zhizhou Shang, Peng Sun, Wei Liu, Xuan Ouyang, dianhai yu, Hao Tian, Hua Wu, Haifeng Wang
We trained the model with 10 billion parameters on a 4TB corpus consisting of plain texts and a large-scale knowledge graph.
1 code implementation • 4 Jun 2021 • Weiyue Su, Xuyi Chen, Shikun Feng, Jiaxiang Liu, Weixin Liu, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Specifically, the first stage, General Distillation, performs distillation with guidance from pretrained teacher, gerenal data and latent distillation loss.
no code implementations • NAACL 2021 • Yu Sun, Shaolin Zhu, Feng Yifan, Chenggang Mi
In this paper, we propose an approach based on transfer learning to mine parallel sentences in the unsupervised setting. With the help of bilingual corpora of rich-resource language pairs, we can mine parallel sentences without bilingual supervision of low-resource language pairs.
no code implementations • 1 Jun 2021 • Md Sadman Sakib, Hailey Baez, David Paulius, Yu Sun
We first automatically convert task trees to recipes, and we then compare them with the human-created recipes in the Recipe1M+ dataset via a survey.
no code implementations • 1 Jun 2021 • David Paulius, Alejandro Agostini, Yu Sun, Dongheui Lee
Following work on joint object-action representations, the functional object-oriented network (FOON) was introduced as a knowledge graph representation for robots.
no code implementations • 23 Apr 2021 • Wu Liu, Qian Bao, Yu Sun, Tao Mei
We believe this survey will provide the readers with a deep and insightful understanding of monocular human pose estimation.
1 code implementation • 9 Feb 2021 • Yu Sun, Jiaming Liu, Mingyang Xie, Brendt Wohlberg, Ulugbek S. Kamilov
We propose Coordinate-based Internal Learning (CoIL) as a new deep-learning (DL) methodology for the continuous representation of measurements.
1 code implementation • 22 Jan 2021 • Jiaming Liu, Yu Sun, Weijie Gan, Xiaojian Xu, Brendt Wohlberg, Ulugbek S. Kamilov
Deep unfolding networks have recently gained popularity in the context of solving imaging inverse problems.
2 code implementations • EMNLP 2021 • Xuan Ouyang, Shuohuan Wang, Chao Pang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
In this paper, we propose ERNIE-M, a new training method that encourages the model to align the representation of multiple languages with monolingual corpora, to overcome the constraint that the parallel corpus size places on the model performance.
Ranked #14 on
Zero-Shot Cross-Lingual Transfer
on XTREME
3 code implementations • ACL 2021 • Siyu Ding, Junyuan Shang, Shuohuan Wang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Transformers are not suited for processing long documents, due to their quadratically increasing memory and time consumption.
Ranked #1000000000 on
Text Classification
on IMDb
no code implementations • 10 Dec 2020 • Maxat Alibayev, David Paulius, Yu Sun
In this work, we propose a motion embedding strategy known as motion codes, which is a vectorized representation of motions based on a manipulation's salient mechanical attributes.
no code implementations • 3 Dec 2020 • Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun
We compare the performance of the multimodal and unimodal postoperative pain assessment, and measure the impact of temporal information integration.
no code implementations • 26 Nov 2020 • Mingyang Xie, Yu Sun, Jiaming Liu, Brendt Wohlberg, Ulugbek S. Kamilov
Cal-RED extends the traditional RED methodology to imaging problems that require the calibration of the measurement operator.
no code implementations • 19 Nov 2020 • Yongqiang Huang, Juan Wilches, Yu Sun
We have also evaluated the proposed self-supervised generalization approach using unaccustomed containers that are far different from the ones in the training set.
no code implementations • 27 Oct 2020 • Yu Sun, Qian Bao, Wu Liu, Wenpeng Gao, Yili Fu, Chuang Gan, Tao Mei
To solve this problem, we design a multi-branch framework to disentangle the regression of different body properties, enabling us to separate each component's training in a synthetic training manner using unpaired data available.
2 code implementations • NAACL 2021 • Dongling Xiao, Yu-Kun Li, Han Zhang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
We argue that such contiguously masking method neglects to model the intra-dependencies and inter-relation of coarse-grained linguistic information.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Xinting Huang, Jianzhong Qi, Yu Sun, Rui Zhang
To alleviate the need of action annotations, latent action learning is introduced to map each utterance to a latent representation.
no code implementations • SEMEVAL 2020 • Shuohuan Wang, Jiaxiang Liu, Xuan Ouyang, Yu Sun
In Sub-task A - Offensive Language Identification, we ranked first in terms of average F1 scores in all languages.
no code implementations • ICLR 2021 • Yu Sun, Jiaming Liu, Yiran Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Regularization by denoising (RED) is a recently developed framework for solving inverse problems by integrating advanced denoisers as image priors.
no code implementations • 29 Sep 2020 • Weijie Gan, Yu Sun, Cihat Eldeniz, Jiaming Liu, Hongyu An, Ulugbek S. Kamilov
One of the key limitations in conventional deep learning based image reconstruction is the need for registered pairs of training images containing a set of high-quality groundtruth images.
no code implementations • 16 Sep 2020 • Yu-Wei Zhan, Xin Luo, Yu Sun, Yongxin Wang, Zhen-Duo Chen, Xin-Shun Xu
However, existing hashing methods for social image retrieval are based on batch mode which violates the nature of social images, i. e., social images are usually generated periodically or collected in a stream fashion.
no code implementations • SEMEVAL 2020 • Zhengjie Huang, Shikun Feng, Weiyue Su, Xuyi Chen, Shuohuan Wang, Jiaxiang Liu, Xuan Ouyang, Yu Sun
This paper describes the system designed by ERNIE Team which achieved the first place in SemEval-2020 Task 10: Emphasis Selection For Written Text in Visual Media.
no code implementations • SEMEVAL 2020 • Jiaxiang Liu, Xuyi Chen, Shikun Feng, Shuohuan Wang, Xuan Ouyang, Yu Sun, Zhengjie Huang, Weiyue Su
Code switching is a linguistic phenomenon that may occur within a multilingual setting where speakers share more than one language.
3 code implementations • 8 Sep 2020 • Yunsheng Shi, Zhengjie Huang, Shikun Feng, Hui Zhong, Wenjin Wang, Yu Sun
Graph neural network (GNN) and label propagation algorithm (LPA) are both message passing algorithms, which have achieved superior performance in semi-supervised classification.
Ranked #1 on
Node Property Prediction
on ogbn-proteins
2 code implementations • ICCV 2021 • Yu Sun, Qian Bao, Wu Liu, Yili Fu, Michael J. Black, Tao Mei
Through a body-center-guided sampling process, the body mesh parameters of all people in the image are easily extracted from the Mesh Parameter map.
Ranked #1 on
3D Multi-Person Mesh Recovery
on Relative Human
(using extra training data)
no code implementations • 31 Jul 2020 • Maxat Alibayev, David Paulius, Yu Sun
A motion taxonomy can encode manipulations as a binary-encoded representation, which we refer to as motion codes.
no code implementations • 13 Jul 2020 • David Paulius, Nicholas Eales, Yu Sun
To represent motions from a mechanical point of view, this paper explores motion embedding using the motion taxonomy.
2 code implementations • ICLR 2021 • Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang
A natural solution would be to keep training after deployment in the new environment, but this cannot be done if the new environment offers no reward signal.
no code implementations • 30 Jun 2020 • Fei Yu, Jiji Tang, Weichong Yin, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Thus, ERNIE-ViL can learn the joint representations characterizing the alignments of the detailed semantics across vision and language.
Ranked #2 on
Visual Question Answering (VQA)
on VCR (QA-R) test
no code implementations • 5 Jun 2020 • Yu Sun, Zihui Wu, Xiaojian Xu, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a broadly applicable methodology for solving inverse problems by exploiting statistical priors specified as denoisers.
no code implementations • 15 May 2020 • Xiaojian Xu, Yu Sun, Jiaming Liu, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a methodology for regularized image reconstruction that specifies the prior through an image denoiser.
no code implementations • ACL 2020 • Xinting Huang, Jianzhong Qi, Yu Sun, Rui Zhang
This approach requires complete state-action annotations of human-to-human dialogues (i. e., expert demonstrations), which is labor intensive.
no code implementations • 7 Apr 2020 • Aoqian Zhang, Shaoxu Song, Yu Sun, Jian-Min Wang
We propose to adaptively learn individual models over various number l of neighbors for different complete tuples.
no code implementations • 24 Mar 2020 • Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun
This paper presents the first investigation into the use of fully automated deep learning framework for assessing neonatal postoperative pain.
6 code implementations • 26 Jan 2020 • Dongling Xiao, Han Zhang, Yukun Li, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
Current pre-training works in natural language generation pay little attention to the problem of exposure bias on downstream tasks.
Ranked #1 on
Question Generation
on SQuAD1.1
(using extra training data)
no code implementations • 18 Dec 2019 • Xinting Huang, Jianzhong Qi, Yu Sun, Rui Zhang
These two components, however, have a discrepancy in their objectives, i. e., task completion and language quality.
no code implementations • 1 Oct 2019 • David Paulius, Yongqiang Huang, Jason Meloncon, Yu Sun
This paper introduces a taxonomy of manipulations as seen especially in cooking for 1) grouping manipulations from the robotics point of view, 2) consolidating aliases and removing ambiguity for motion types, and 3) provide a path to transferring learned manipulations to new unlearned manipulations.
3 code implementations • 29 Sep 2019 • Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt
In this paper, we propose Test-Time Training, a general approach for improving the performance of predictive models when training and test data come from different distributions.
Ranked #34 on
Language Modelling
on LAMBADA
Building change detection for remote sensing images
CARLA MAP Leaderboard
+6
3 code implementations • 26 Sep 2019 • Yu Sun, Eric Tzeng, Trevor Darrell, Alexei A. Efros
This paper addresses unsupervised domain adaptation, the setting where labeled training data is available on a source domain, but the goal is to have good performance on a target domain with only unlabeled data.
no code implementations • 25 Sep 2019 • Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt
We introduce a general approach, called test-time training, for improving the performance of predictive models when test and training data come from different distributions.
no code implementations • 20 Sep 2019 • Jiaming Liu, Yu Sun, Ulugbek S. Kamilov
We introduce a new algorithm for regularized reconstruction of multispectral (MS) images from noisy linear measurements.
no code implementations • 5 Sep 2019 • Md Sirajus Salekin, Ghada Zamzmi, Rahul Paul, Dmitry Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun
Neonatal pain assessment in clinical environments is challenging as it is discontinuous and biased.
no code implementations • 4 Sep 2019 • Zihui Wu, Yu Sun, Jiaming Liu, Ulugbek S. Kamilov
Regularization by denoising (RED) is a powerful framework for solving imaging inverse problems.
no code implementations • 25 Aug 2019 • Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi, Thao Ho, Yu Sun
Neonates do not have the ability to either articulate pain or communicate it non-verbally by pointing.
no code implementations • 3 Aug 2019 • Xinting Huang, Jianzhong Qi, Yu Sun, Rui Zhang, Hai-Tao Zheng
To model and utilize the context information for aggregated search, we propose a model with context attention and representation learning (CARL).
3 code implementations • 29 Jul 2019 • Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Hao Tian, Hua Wu, Haifeng Wang
Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language processing.
Ranked #1 on
Chinese Sentence Pair Classification
on LCQMC Dev
Chinese Named Entity Recognition
Chinese Reading Comprehension
+8
no code implementations • 24 Jul 2019 • Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz, Yu Sun, Aaron Flores
Conversion prediction plays an important role in online advertising since Cost-Per-Action (CPA) has become one of the primary campaign performance objectives in the industry.
no code implementations • 22 Jun 2019 • Chen Zheng, Yu Sun, Shengxian Wan, dianhai yu
This paper proposes a novel End-to-End neural ranking framework called Reinforced Long Text Matching (RLTM) which matches a query with long documents efficiently and effectively.
no code implementations • 21 Jun 2019 • Yongqiang Huang, Yu Sun
Pouring is the second most frequently executed motion in cooking scenarios.
no code implementations • SEMEVAL 2019 • Jiaxiang Liu, Shuohuan Wang, Yu Sun
This paper describes our system partici- pated in Task 9 of SemEval-2019: the task is focused on suggestion mining and it aims to classify given sentences into sug- gestion and non-suggestion classes in do- main specific and cross domain training setting respectively.
no code implementations • 1 Jun 2019 • Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi
In recommender systems, usually the ratings of a user to most items are missing and a critical problem is that the missing ratings are often missing not at random (MNAR) in reality.
no code implementations • 13 May 2019 • Ahmad Babaeian Jelodar, Yu Sun
The pipeline presented in this paper includes a CNN with a double classification layer and the Concept-Net language knowledge graph on top.
1 code implementation • NeurIPS 2019 • Yu Sun, Jiaming Liu, Ulugbek S. Kamilov
In this work, we develop a new block coordinate RED algorithm that decomposes a large-scale estimation problem into a sequence of updates over a small subset of the unknown variables.
1 code implementation • 1 May 2019 • David Paulius, Kelvin Sheng Pei Dong, Yu Sun
The paper also presents a task planning algorithm for the weighted FOON to allocate manipulation action load to the robot and human to achieve optimal performance while minimizing human effort.
19 code implementations • 19 Apr 2019 • Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, Hua Wu
We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration).
Ranked #3 on
Natural Language Inference
on XNLI Chinese Dev
Chinese Named Entity Recognition
Chinese Sentence Pair Classification
+8
no code implementations • NeurIPS 2018 • Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi
An alternative method is to adversarially train the classifier against a discriminator in a two-player game akin to generative adversarial networks (GAN), which can ensure the classifier to learn the true data distribution at the equilibrium of this game.
no code implementations • 8 Nov 2018 • Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a popular framework for regularized signal reconstruction by using advanced denoisers within an iterative algorithm.
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 • 31 Oct 2018 • Yu Sun, Shiqi Xu, Yunzhe Li, Lei Tian, Brendt Wohlberg, Ulugbek S. Kamilov
The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm.
no code implementations • 30 Oct 2018 • Jiaming Liu, Yu Sun, Xiaojian Xu, Ulugbek S. Kamilov
In the past decade, sparsity-driven regularization has led to significant improvements in image reconstruction.
1 code implementation • 12 Sep 2018 • Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
The results in this paper have the potential to expand the applicability of the PnP framework to very large and redundant datasets.
2 code implementations • 22 Aug 2018 • Yu Sun, Siv G. E. Andersson
Background Synonymous codon choice is mainly affected by mutation and selection.
Genomics
no code implementations • 5 Jul 2018 • David Paulius, Yu Sun
Within the realm of service robotics, researchers have placed a great amount of effort into learning, understanding, and representing motions as manipulations for task execution by robots.
1 code implementation • 5 Jul 2018 • David Paulius, Ahmad Babaeian Jelodar, Yu Sun
To further improve the performance of knowledge retrieval as a follow up to our previous work, we discuss generalizing knowledge to be applied to objects which are similar to what we have in FOON without manually annotating new sources of knowledge.
no code implementations • 4 Jul 2018 • Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi, Yu Sun
In this paper, we propose a new pipeline for pain expression recognition in neonates using transfer learning.
no code implementations • 3 Jul 2018 • Ahmad Babaeian Jelodar, David Paulius, Yu Sun
Each action is therefore associated with a functional unit and the sequence of actions is further evaluated to identify the single on-going activity in the video.
no code implementations • 20 Jun 2018 • Yu Sun, Ulugbek S. Kamilov
The problem of image reconstruction under multiple light scattering is usually formulated as a regularized non-convex optimization.
5 code implementations • ICLR 2018 • Qiantong Xu, Gao Huang, Yang Yuan, Chuan Guo, Yu Sun, Felix Wu, Kilian Weinberger
Evaluating generative adversarial networks (GANs) is inherently challenging.
5 code implementations • 9 Jun 2018 • Junwei Pan, Jian Xu, Alfonso Lobos Ruiz, Wenliang Zhao, Shengjun Pan, Yu Sun, Quan Lu
The data involved in CTR prediction are typically multi-field categorical data, i. e., every feature is categorical and belongs to one and only one field.
no code implementations • 5 Jun 2018 • Hang Liu, Hengyu Li, Jun Luo, Shaorong Xie, Yu Sun
A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image.
no code implementations • 17 May 2018 • Ahmad Babaeian Jelodar, Md Sirajus Salekin, Yu Sun
The trained state identification model is evaluated on a subset of the Imagenet dataset and state labels are provided using a combination of the model with manual checking.
4 code implementations • 18 Mar 2018 • Yu Sun, Zhihao Xia, Ulugbek S. Kamilov
Image reconstruction under multiple light scattering is crucial in a number of applications such as diffraction tomography.
16 code implementations • ICML 2017 • Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger
Confidence calibration -- the problem of predicting probability estimates representative of the true correctness likelihood -- is important for classification models in many applications.
no code implementations • 25 May 2017 • Yongqiang Huang, Yu Sun
We present a pouring trajectory generation approach, which uses force feedback from the cup to determine the future velocity of pouring.
no code implementations • 26 Mar 2017 • Xiaowei Zhang, Xudong Shi, Yu Sun, Li Cheng
Our model first takes a correction step on the grossly corrupted responses via geodesic curves on the manifold, and then performs multivariate linear regression on the corrected data.
no code implementations • 12 Feb 2017 • Yu Sun, Ke Tang, Zexuan Zhu, Xin Yao
Incremental learning with concept drift has often been tackled by ensemble methods, where models built in the past can be re-trained to attain new models for the current data.
1 code implementation • NeurIPS 2016 • Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger
Accurately measuring the similarity between text documents lies at the core of many real world applications of machine learning.
no code implementations • 8 Sep 2016 • Matteo Bianchi, Jeannette Bohg, Yu Sun
This paper reports the activities and outcomes in the Workshop on Grasping and Manipulation Datasets that was organized under the International Conference on Robotics and Automation (ICRA) 2016.
no code implementations • 1 Jul 2016 • Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi, Yu Sun, Terri Ashmeade
In addition, it reviews the databases available to the research community and discusses the current limitations of the automated pain assessment.
2 code implementations • TACL 2018 • Xilun Chen, Yu Sun, Ben Athiwaratkun, Claire Cardie, Kilian Weinberger
To tackle the sentiment classification problem in low-resource languages without adequate annotated data, we propose an Adversarial Deep Averaging Network (ADAN) to transfer the knowledge learned from labeled data on a resource-rich source language to low-resource languages where only unlabeled data exists.
15 code implementations • 30 Mar 2016 • Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Weinberger
With stochastic depth we can increase the depth of residual networks even beyond 1200 layers and still yield meaningful improvements in test error (4. 91% on CIFAR-10).
Ranked #20 on
Image Classification
on SVHN
no code implementations • 17 Dec 2015 • Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger
Causal inference has the potential to have significant impact on medical research, prevention and control of diseases, and identifying factors that impact economic changes to name just a few.
no code implementations • 30 Jun 2014 • Yu Sun, Louis F. Rossi, Chien-Chung Shen, Jennifer Miller, X. Rosalind Wang, Joseph T. Lizier, Mikhail Prokopenko, Upul Senanayake
Depending upon the leadership model, leaders can use their external information either all the time or in response to local conditions [Couzin et al. 2005; Sun et al. 2013].