no code implementations • ICML 2020 • Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO
Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.
1 code implementation • EMNLP 2021 • Yuan YAO, Jiaju Du, Yankai Lin, Peng Li, Zhiyuan Liu, Jie zhou, Maosong Sun
Existing relation extraction (RE) methods typically focus on extracting relational facts between entity pairs within single sentences or documents.
no code implementations • 19 Apr 2024 • Wei W. Xing, Weijian Fan, Zhuohua Liu, Yuan YAO, Yuanqi Hu
Automatic transistor sizing in circuit design continues to be a formidable challenge.
no code implementations • 17 Apr 2024 • Minghe Gao, Shuang Chen, Liang Pang, Yuan YAO, Jisheng Dang, Wenqiao Zhang, Juncheng Li, Siliang Tang, Yueting Zhuang, Tat-Seng Chua
Their ability to execute intricate compositional reasoning tasks is also constrained, culminating in a stagnation of learning progression for these models.
2 code implementations • 9 Apr 2024 • Shengding Hu, Yuge Tu, Xu Han, Chaoqun He, Ganqu Cui, Xiang Long, Zhi Zheng, Yewei Fang, Yuxiang Huang, Weilin Zhao, Xinrong Zhang, Zheng Leng Thai, Kaihuo Zhang, Chongyi Wang, Yuan YAO, Chenyang Zhao, Jie zhou, Jie Cai, Zhongwu Zhai, Ning Ding, Chao Jia, Guoyang Zeng, Dahai Li, Zhiyuan Liu, Maosong Sun
For data scaling, we introduce a Warmup-Stable-Decay (WSD) learning rate scheduler (LRS), conducive to continuous training and domain adaptation.
2 code implementations • 18 Mar 2024 • Ruyi Xu, Yuan YAO, Zonghao Guo, Junbo Cui, Zanlin Ni, Chunjiang Ge, Tat-Seng Chua, Zhiyuan Liu, Maosong Sun, Gao Huang
To address the challenges, we present LLaVA-UHD, a large multimodal model that can efficiently perceive images in any aspect ratio and high resolution.
1 code implementation • 13 Mar 2024 • Xingyu Lu, He Cao, Zijing Liu, Shengyuan Bai, Leqing Chen, Yuan YAO, Hai-Tao Zheng, Yu Li
Large language models are playing an increasingly significant role in molecular research, yet existing models often generate erroneous information, posing challenges to accurate molecular comprehension.
1 code implementation • 1 Mar 2024 • Zenan Li, Yuan YAO, Taolue Chen, Jingwei Xu, Chun Cao, Xiaoxing Ma, Jian Lü
Neuro-symbolic learning generally consists of two separated worlds, i. e., neural network training and symbolic constraint solving, whose success hinges on symbol grounding, a fundamental problem in AI.
1 code implementation • 1 Mar 2024 • Zenan Li, Zehua Liu, Yuan YAO, Jingwei Xu, Taolue Chen, Xiaoxing Ma, Jian Lü
In this paper, we present a new framework for learning with logical constraints.
no code implementations • 26 Feb 2024 • Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan YAO
In this work, we aim to address this alignment challenge for conditional generation tasks.
1 code implementation • 9 Feb 2024 • Gongxi Zhu, Donghao Li, Hanlin Gu, Yuxing Han, Yuan YAO, Lixin Fan, Qiang Yang
Firstly, combining model information from multiple communication rounds (Multi-temporal) enhances the overall effectiveness of MIAs compared to utilizing model information from a single epoch.
no code implementations • 5 Jan 2024 • Daoan Zhang, Junming Yang, Hanjia Lyu, Zijian Jin, Yuan YAO, Mingkai Chen, Jiebo Luo
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image inputs.
Ranked #3 on Visual Reasoning on Winoground
no code implementations • 2 Jan 2024 • Yifang Men, Biwen Lei, Yuan YAO, Miaomiao Cui, Zhouhui Lian, Xuansong Xie
We present En3D, an enhanced generative scheme for sculpting high-quality 3D human avatars.
no code implementations • 13 Dec 2023 • Yuan YAO, Tian-Sheuan Chang
Furthermore, the hardware architecture scales effectively, with only a sublinear increase in area cost.
no code implementations • 8 Dec 2023 • Mengyang Feng, Jinlin Liu, Kai Yu, Yuan YAO, Zheng Hui, Xiefan Guo, Xianhui Lin, Haolan Xue, Chen Shi, Xiaowen Li, Aojie Li, Xiaoyang Kang, Biwen Lei, Miaomiao Cui, Peiran Ren, Xuansong Xie
In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos.
2 code implementations • 1 Dec 2023 • Tianyu Yu, Yuan YAO, Haoye Zhang, Taiwen He, Yifeng Han, Ganqu Cui, Jinyi Hu, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun, Tat-Seng Chua
Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction.
1 code implementation • 27 Nov 2023 • He Cao, Zijing Liu, Xingyu Lu, Yuan YAO, Yu Li
The rapid evolution of artificial intelligence in drug discovery encounters challenges with generalization and extensive training, yet Large Language Models (LLMs) offer promise in reshaping interactions with complex molecular data.
Ranked #20 on Molecule Captioning on ChEBI-20
1 code implementation • 21 Nov 2023 • Yunpeng Huang, Jingwei Xu, Junyu Lai, Zixu Jiang, Taolue Chen, Zenan Li, Yuan YAO, Xiaoxing Ma, Lijuan Yang, Hao Chen, Shupeng Li, Penghao Zhao
Transformer-based Large Language Models (LLMs) have been applied in diverse areas such as knowledge bases, human interfaces, and dynamic agents, and marking a stride towards achieving Artificial General Intelligence (AGI).
1 code implementation • 8 Nov 2023 • Ao Zhang, Yuan YAO, Wei Ji, Zhiyuan Liu, Tat-Seng Chua
The development of large language models (LLMs) has greatly advanced the field of multimodal understanding, leading to the emergence of large multimodal models (LMMs).
no code implementations • 20 Oct 2023 • Zekai Qu, Ruobing Xie, Chaojun Xiao, Yuan YAO, Zhiyuan Liu, Fengzong Lian, Zhanhui Kang, Jie zhou
With the thriving of pre-trained language model (PLM) widely verified in various of NLP tasks, pioneer efforts attempt to explore the possible cooperation of the general textual information in PLM with the personalized behavioral information in user historical behavior sequences to enhance sequential recommendation (SR).
2 code implementations • 1 Oct 2023 • Tianyu Yu, Jinyi Hu, Yuan YAO, Haoye Zhang, Yue Zhao, Chongyi Wang, Shan Wang, Yinxv Pan, Jiao Xue, Dahai Li, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun
The capabilities of MLLMs depend on two crucial factors: the model architecture to facilitate the feature alignment of visual modules and large language models; the multimodal instruction tuning datasets for human instruction following.
no code implementations • 23 Sep 2023 • Haibo Ye, Xinjie Li, Yuan YAO, Hanghang Tong
In recommender systems, knowledge graph (KG) can offer critical information that is lacking in the original user-item interaction graph (IG).
no code implementations • 12 Sep 2023 • Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan YAO, Tong Zhang
Building on the analysis and the observation that averaging different layers of the transformer leads to significantly different reward-tax trade-offs, we propose Adaptive Model Averaging (AMA) to adaptively find various combination ratios of model layers.
no code implementations • 5 Sep 2023 • Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan YAO, Tong Zhang
Our proposed method, COPS (unCertainty based OPtimal Sub-sampling), is designed to minimize the expected loss of a model trained on subsampled data.
1 code implementation • 28 Aug 2023 • Yang Liu, Cheng Yu, Lei Shang, Yongyi He, Ziheng Wu, Xingjun Wang, Chao Xu, Haoyu Xie, Weida Wang, Yuze Zhao, Lin Zhu, Chen Cheng, Weitao Chen, Yuan YAO, Wenmeng Zhou, Jiaqi Xu, Qiang Wang, Yingda Chen, Xuansong Xie, Baigui Sun
In this paper, we present FaceChain, a personalized portrait generation framework that combines a series of customized image-generation model and a rich set of face-related perceptual understanding models (\eg, face detection, deep face embedding extraction, and facial attribute recognition), to tackle aforementioned challenges and to generate truthful personalized portraits, with only a handful of portrait images as input.
2 code implementations • 23 Aug 2023 • Jinyi Hu, Yuan YAO, Chongyi Wang, Shan Wang, Yinxu Pan, Qianyu Chen, Tianyu Yu, Hanghao Wu, Yue Zhao, Haoye Zhang, Xu Han, Yankai Lin, Jiao Xue, Dahai Li, Zhiyuan Liu, Maosong Sun
Building a competitive counterpart in other languages is highly challenging due to the low-resource nature of non-English multimodal data (i. e., lack of large-scale, high-quality image-text data).
no code implementations • 2 Aug 2023 • Jiamin Wu, He Cao, Yuan YAO
Examples of such side information include the chemical and geometric features of the target protein, ligand-target compound interactions, and ligand chemical properties.
no code implementations • 16 Jun 2023 • Qingshuang Sun, Denis Steckelmacher, Yuan YAO, Ann Nowé, Raphaël Avalos
Communication plays a vital role in multi-agent systems, fostering collaboration and coordination.
1 code implementation • 15 Jun 2023 • Jifan Yu, Xiaozhi Wang, Shangqing Tu, Shulin Cao, Daniel Zhang-li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Nianyi Lin, Kaifeng Yun, Linlu Gong, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan YAO, Ning Ding, Lei Hou, Zhiyuan Liu, Bin Xu, Jie Tang, Juanzi Li
The unprecedented performance of large language models (LLMs) necessitates improvements in evaluations.
no code implementations • 5 May 2023 • Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan YAO
In this paper, we aim to bridge this gap by presenting a framework for random smoothing regularization that can adaptively and effectively learn a wide range of ground truth functions belonging to the classical Sobolev spaces.
1 code implementation • NeurIPS 2023 • Ao Zhang, Hao Fei, Yuan YAO, Wei Ji, Li Li, Zhiyuan Liu, Tat-Seng Chua
While developing a new multimodal LLM (MLLM) by pre-training on tremendous image-text pairs from scratch can be exceedingly resource-consuming, connecting an existing LLM with a comparatively lightweight visual prompt generator (VPG) becomes a feasible paradigm.
1 code implementation • 24 Feb 2023 • Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Lujia Pan, Yuan YAO
One of the reasons is that the learned representations (i. e. features) from the imbalanced datasets are less effective than those from balanced datasets.
no code implementations • 29 Dec 2022 • Yuan Zhang, Jianhua Zhang, Yuxiang Zhang, Yuan YAO, Guangyi Liu
However, the channel might not satisfy isotropic scattering because of generalized angle distributions, and the antenna gain is limited by the array aperture in reality.
no code implementations • 28 Dec 2022 • He Cao, Jianan Wang, Tianhe Ren, Xianbiao Qi, Yihao Chen, Yuan YAO, Lei Zhang
We further provide a hypothesis on the implication of disentangling the generative backbone as an encoder-decoder structure and show proof-of-concept experiments verifying the effectiveness of a stronger encoder for generative tasks with ASymmetriC ENcoder Decoder (ASCEND).
no code implementations • 17 Dec 2022 • Yuan YAO, Yuanhan Zhang, Zhenfei Yin, Jiebo Luo, Wanli Ouyang, Xiaoshui Huang
The recent success of pre-trained 2D vision models is mostly attributable to learning from large-scale datasets.
no code implementations • ICCV 2023 • Yong-Lu Li, Yue Xu, Xinyu Xu, Xiaohan Mao, Yuan YAO, SiQi Liu, Cewu Lu
To support OCL, we build a densely annotated knowledge base including extensive labels for three levels of object concept (category, attribute, affordance), and the causal relations of three levels.
1 code implementation • 22 Nov 2022 • Yuan YAO, Tianyu Yu, Ao Zhang, Mengdi Li, Ruobing Xie, Cornelius Weber, Zhiyuan Liu, Hai-Tao Zheng, Stefan Wermter, Tat-Seng Chua, Maosong Sun
In this work, we present CLEVER, which formulates CKE as a distantly supervised multi-instance learning problem, where models learn to summarize commonsense relations from a bag of images about an entity pair without any human annotation on image instances.
no code implementations • 11 Nov 2022 • Jinshan Zeng, Yefei Wang, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan YAO
The effectiveness of the proposed model for the zero-shot traditional Chinese font generation is also evaluated in this paper.
3 code implementations • ICCV 2023 • Changjiang Li, Ren Pang, Zhaohan Xi, Tianyu Du, Shouling Ji, Yuan YAO, Ting Wang
As a new paradigm in machine learning, self-supervised learning (SSL) is capable of learning high-quality representations of complex data without relying on labels.
no code implementations • 20 Sep 2022 • Shihe Wang, Jianfeng Ren, Ruibin Bai, Yuan YAO, Xudong Jiang
Thus, we propose a Max-Dependency-Min-Divergence (MDmD) criterion that maximizes both the discriminant information and generalization ability of the discretized data.
no code implementations • 13 Aug 2022 • Tong Wang, Yuan YAO, Feng Xu, Miao Xu, Shengwei An, Ting Wang
Existing defenses are mainly built upon the observation that the backdoor trigger is usually of small size or affects the activation of only a few neurons.
1 code implementation • 6 Jul 2022 • Yuan YAO, Fengze Liu, Zongwei Zhou, Yan Wang, Wei Shen, Alan Yuille, Yongyi Lu
Previous methods proposed Variational Autoencoder (VAE) based models to learn the distribution of shape for a particular organ and used it to automatically evaluate the quality of a segmentation prediction by fitting it into the learned shape distribution.
3 code implementations • 6 Jul 2022 • Yifang Men, Yuan YAO, Miaomiao Cui, Zhouhui Lian, Xuansong Xie
This paper introduces DCT-Net, a novel image translation architecture for few-shot portrait stylization.
1 code implementation • 16 Jun 2022 • Yuxuan Han, Zhicong Liang, Zhipeng Liang, Yang Wang, Yuan YAO, Jiheng Zhang
To address such a challenge as the online convex optimization with privacy protection, we propose a private variant of online Frank-Wolfe algorithm with recursive gradients for variance reduction to update and reveal the parameters upon each data.
1 code implementation • Findings (ACL) 2022 • Yuan YAO, Bowen Dong, Ao Zhang, Zhengyan Zhang, Ruobing Xie, Zhiyuan Liu, Leyu Lin, Maosong Sun, Jianyong Wang
Recent works have shown promising results of prompt tuning in stimulating pre-trained language models (PLMs) for natural language processing (NLP) tasks.
1 code implementation • 23 May 2022 • Yuan YAO, Qianyu Chen, Ao Zhang, Wei Ji, Zhiyuan Liu, Tat-Seng Chua, Maosong Sun
We show that PEVL enables state-of-the-art performance of detector-free VLP models on position-sensitive tasks such as referring expression comprehension and phrase grounding, and also improves the performance on position-insensitive tasks with grounded inputs.
Ranked #1 on Visual Commonsense Reasoning on VCR (Q-AR) test
no code implementations • 21 Apr 2022 • Senrong Xu, Yuan YAO, Liangyue Li, Wei Yang, Feng Xu, Hanghang Tong
In this work, we study the victim node detection problem under topology attacks against GNNs.
no code implementations • 26 Mar 2022 • Sha Yuan, Hanyu Zhao, Shuai Zhao, Jiahong Leng, Yangxiao Liang, Xiaozhi Wang, Jifan Yu, Xin Lv, Zhou Shao, Jiaao He, Yankai Lin, Xu Han, Zhenghao Liu, Ning Ding, Yongming Rao, Yizhao Gao, Liang Zhang, Ming Ding, Cong Fang, Yisen Wang, Mingsheng Long, Jing Zhang, Yinpeng Dong, Tianyu Pang, Peng Cui, Lingxiao Huang, Zheng Liang, HuaWei Shen, HUI ZHANG, Quanshi Zhang, Qingxiu Dong, Zhixing Tan, Mingxuan Wang, Shuo Wang, Long Zhou, Haoran Li, Junwei Bao, Yingwei Pan, Weinan Zhang, Zhou Yu, Rui Yan, Chence Shi, Minghao Xu, Zuobai Zhang, Guoqiang Wang, Xiang Pan, Mengjie Li, Xiaoyu Chu, Zijun Yao, Fangwei Zhu, Shulin Cao, Weicheng Xue, Zixuan Ma, Zhengyan Zhang, Shengding Hu, Yujia Qin, Chaojun Xiao, Zheni Zeng, Ganqu Cui, Weize Chen, Weilin Zhao, Yuan YAO, Peng Li, Wenzhao Zheng, Wenliang Zhao, Ziyi Wang, Borui Zhang, Nanyi Fei, Anwen Hu, Zenan Ling, Haoyang Li, Boxi Cao, Xianpei Han, Weidong Zhan, Baobao Chang, Hao Sun, Jiawen Deng, Chujie Zheng, Juanzi Li, Lei Hou, Xigang Cao, Jidong Zhai, Zhiyuan Liu, Maosong Sun, Jiwen Lu, Zhiwu Lu, Qin Jin, Ruihua Song, Ji-Rong Wen, Zhouchen Lin, LiWei Wang, Hang Su, Jun Zhu, Zhifang Sui, Jiajun Zhang, Yang Liu, Xiaodong He, Minlie Huang, Jian Tang, Jie Tang
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.
2 code implementations • 22 Mar 2022 • Ao Zhang, Yuan YAO, Qianyu Chen, Wei Ji, Zhiyuan Liu, Maosong Sun, Tat-Seng Chua
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images.
Ranked #1 on Predicate Classification on Visual Genome
1 code implementation • CVPR 2022 • Jianqiang Ren, Yuan YAO, Biwen Lei, Miaomiao Cui, Xuansong Xie
Body reshaping is an important procedure in portrait photo retouching.
1 code implementation • 14 Feb 2022 • Donghao Li, Yang Cao, Yuan YAO
To further enhance the utility and address the label collapse issue when the mixup degree is large, we propose a Hierarchical sampling method to stratify the mixup samples on a small number of classes.
no code implementations • CVPR 2022 • Yifang Men, Yuan YAO, Miaomiao Cui, Zhouhui Lian, Xuansong Xie, Xian-Sheng Hua
Experimental results demonstrate the superiority of the proposed method over the state of the art and validate its effectiveness in the brand-new task of general cartoon image synthesis.
no code implementations • 27 Dec 2021 • Yuan YAO, Qingxiu Dong, Jian Guan, Boxi Cao, Zhengyan Zhang, Chaojun Xiao, Xiaozhi Wang, Fanchao Qi, Junwei Bao, Jinran Nie, Zheni Zeng, Yuxian Gu, Kun Zhou, Xuancheng Huang, Wenhao Li, Shuhuai Ren, Jinliang Lu, Chengqiang Xu, Huadong Wang, Guoyang Zeng, Zile Zhou, Jiajun Zhang, Juanzi Li, Minlie Huang, Rui Yan, Xiaodong He, Xiaojun Wan, Xin Zhao, Xu sun, Yang Liu, Zhiyuan Liu, Xianpei Han, Erhong Yang, Zhifang Sui, Maosong Sun
We argue that for general-purpose language intelligence evaluation, the benchmark itself needs to be comprehensive and systematic.
1 code implementation • 22 Nov 2021 • Tong Wang, Yuan YAO, Feng Xu, Shengwei An, Hanghang Tong, Ting Wang
We also evaluate FTROJAN against state-of-the-art defenses as well as several adaptive defenses that are designed on the frequency domain.
no code implementations • 27 Sep 2021 • Hanlin Gu, Lixin Fan, Bowen Li, Yan Kang, Yuan YAO, Qiang Yang
To address the aforementioned perplexity, we propose a novel Bayesian Privacy (BP) framework which enables Bayesian restoration attacks to be formulated as the probability of reconstructing private data from observed public information.
1 code implementation • 24 Sep 2021 • Yuan YAO, Ao Zhang, Zhengyan Zhang, Zhiyuan Liu, Tat-Seng Chua, Maosong Sun
Pre-Trained Vision-Language Models (VL-PTMs) have shown promising capabilities in grounding natural language in image data, facilitating a broad variety of cross-modal tasks.
1 code implementation • 14 Jul 2021 • Wenqi Zeng, Siqin Cao, Xuhui Huang, Yuan YAO
Therefore, to learn rare events of slow molecular dynamics by LSTM and Transformer, it is critical to choose proper temporal resolution (i. e., saving intervals of MD simulation trajectories) and state partition in high resolution data, since deep neural network models might not automatically disentangle slow dynamics from fast dynamics when both are present in data influencing each other.
2 code implementations • 20 Jun 2021 • Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan YAO, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun
We present a suite of cost-effective techniques for the use of PLMs to deal with the efficiency issues of pre-training, fine-tuning, and inference.
no code implementations • 14 Jun 2021 • Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Yuan YAO, Ao Zhang, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, Jun Zhu
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI).
1 code implementation • ACL 2021 • Fanchao Qi, Yuan YAO, Sophia Xu, Zhiyuan Liu, Maosong Sun
Recent studies show that neural natural language processing (NLP) models are vulnerable to backdoor attacks.
1 code implementation • NAACL 2021 • Kai Zhang, Yuan YAO, Ruobing Xie, Xu Han, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun
To establish the bidirectional connections between OpenRE and relation hierarchy, we propose the task of open hierarchical relation extraction and present a novel OHRE framework for the task.
no code implementations • 31 May 2021 • Xiaoguang Tu, Yingtian Zou, Jian Zhao, Wenjie Ai, Jian Dong, Yuan YAO, Zhikang Wang, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng
Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.
1 code implementation • ICCV 2021 • Yuan YAO, Ao Zhang, Xu Han, Mengdi Li, Cornelius Weber, Zhiyuan Liu, Stefan Wermter, Maosong Sun
In this work, we propose visual distant supervision, a novel paradigm of visual relation learning, which can train scene graph models without any human-labeled data.
no code implementations • 22 Feb 2021 • Chaojun Xiao, Ruobing Xie, Yuan YAO, Zhiyuan Liu, Maosong Sun, Xu Zhang, Leyu Lin
Existing sequential recommendation methods rely on large amounts of training data and usually suffer from the data sparsity problem.
no code implementations • 2 Feb 2021 • Yuan YAO, Wing-Hung Ki, Chi-Ying Tsui
A thorough analysis is done for the ideal and practical scenario and it shows that a mismatched secondary LC tank will affect the communication range and communication correctness.
no code implementations • 1 Jan 2021 • Jinshan Zeng, Yixuan Zha, Ke Ma, Yuan YAO
In this paper, we fill this gap via exploiting a new semi-stochastic variant of the original SVRG with Option I adapted to the semidefinite optimization.
1 code implementation • 16 Dec 2020 • Jinshan Zeng, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan YAO
However, these deep generative models may suffer from the mode collapse issue, which significantly degrades the diversity and quality of generated results.
no code implementations • 15 Dec 2020 • Yuan YAO, Xiaolin Sun
We first review the exact solution of conventional linear quadratic regulation with a linear transition and a Gaussian noise, whose optimal policy does not depend on the Gaussian noise, which is an undesired feature in the presence of significant noises.
no code implementations • 14 Dec 2020 • Yuan YAO, Akira Furusaki
We formulate a $\mathbb{Z}_k$-parafermionization/bosonization scheme for one-dimensional lattice models and field theories on a torus, starting from a generalized Jordan-Wigner transformation on a lattice, which extends the Majorana-Ising duality at $k=2$.
Strongly Correlated Electrons Statistical Mechanics High Energy Physics - Theory Mathematical Physics Mathematical Physics
1 code implementation • NeurIPS 2020 • Long Chen, Yuan YAO, Feng Xu, Miao Xu, Hanghang Tong
Collaborative filtering has been widely used in recommender systems.
1 code implementation • COLING 2020 • Bowen Dong, Yuan YAO, Ruobing Xie, Tianyu Gao, Xu Han, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun
Few-shot classification requires classifiers to adapt to new classes with only a few training instances.
2 code implementations • EMNLP 2021 • Fanchao Qi, Yangyi Chen, Mukai Li, Yuan YAO, Zhiyuan Liu, Maosong Sun
Nevertheless, there are few studies on defending against textual backdoor attacks.
1 code implementation • EMNLP 2020 • Chaojun Xiao, Yuan YAO, Ruobing Xie, Xu Han, Zhiyuan Liu, Maosong Sun, Fen Lin, Leyu Lin
Distant supervision (DS) has been widely used to generate auto-labeled data for sentence-level relation extraction (RE), which improves RE performance.
1 code implementation • 28 Sep 2020 • Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, Yuan YAO
Even replacing only the first layer of a ResNet by such a ODE block can exhibit further improvement in robustness, e. g., under PGD-20 ($\ell_\infty=0. 031$) attack on CIFAR-10 dataset, it achieves 91. 57\% and natural accuracy and 62. 35\% robust accuracy, while a counterpart architecture of ResNet trained with TRADES achieves natural and robust accuracy 76. 29\% and 45. 24\%, respectively.
no code implementations • 19 Sep 2020 • Zheni Zeng, Chaojun Xiao, Yuan YAO, Ruobing Xie, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun
Recommender systems aim to provide item recommendations for users, and are usually faced with data sparsity problem (e. g., cold start) in real-world scenarios.
1 code implementation • 17 Aug 2020 • Hanlin Gu, Yin Xian, Ilona Christy Unarta, Yuan YAO
Equipped with robust $\ell_1$ Autoencoder and some designs of robust $\beta$-GANs, one can stabilize the training of GANs and achieve the state-of-the-art performance of robust denoising with low SNR data and against possible information contamination.
1 code implementation • 6 Aug 2020 • Yuan Yao, Xutao Li, Yu Zhang, Yunming Ye
In reality, however, it is not uncommon to obtain samples from multiple heterogeneous domains.
no code implementations • 17 Jul 2020 • Xinwei Sun, Wenjing Han, Lingjing Hu, Yuan YAO, Yizhou Wang
Specifically, with a variable the splitting term, two estimators are introduced and split apart, i. e. one is for feature selection (the sparse estimator) and the other is for prediction (the dense estimator).
2 code implementations • 15 Jul 2020 • Yikai Wang, Li Zhang, Yuan YAO, Yanwei Fu
We rank the credibility of pseudo-labeled instances along the regularization path of their corresponding incidental parameters, and the most trustworthy pseudo-labeled examples are preserved as the augmented labeled instances.
1 code implementation • 4 Jul 2020 • Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO
Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.
1 code implementation • 24 Jun 2020 • Stefan Heinrich, Yuan YAO, Tobias Hinz, Zhiyuan Liu, Thomas Hummel, Matthias Kerzel, Cornelius Weber, Stefan Wermter
From a neuroscientific perspective, natural language is embodied, grounded in most, if not all, sensory and sensorimotor modalities, and acquired by means of crossmodal integration.
1 code implementation • 20 Jun 2020 • Yuan Yao, Chang Liu, Dezhao Luo, Yu Zhou, Qixiang Ye
The generative perception model acts as a feature decoder to focus on comprehending high temporal resolution and short-term representation by introducing a motion-attention mechanism.
1 code implementation • CVPR 2020 • Yuan Yao, Chang Liu, Dezhao Luo, Yu Zhou, Qixiang Ye
The generative perception model acts as a feature decoder to focus on comprehending high temporal resolution and short-term representation by introducing a motion-attention mechanism.
no code implementations • 1 May 2020 • Zhicong Liang, Bao Wang, Quanquan Gu, Stanley Osher, Yuan YAO
Federated learning aims to protect data privacy by collaboratively learning a model without sharing private data among users.
1 code implementation • CVPR 2020 • Jinlin Liu, Yuan YAO, Wendi Hou, Miaomiao Cui, Xuansong Xie, Chang-Shui Zhang, Xian-Sheng Hua
In this paper, we propose to use coarse annotated data coupled with fine annotated data to boost end-to-end semantic human matting without trimaps as extra input.
Ranked #9 on Image Matting on AM-2K
no code implementations • 24 Feb 2020 • Jiefu Zhang, Leonardo Zepeda-Núñez, Yuan YAO, Lin Lin
When such structural information is not available, and we may only use a dense neural network, the optimization procedure to find the sparse network embedded in the dense network is similar to finding the needle in a haystack, using a given number of samples of the function.
1 code implementation • CVPR 2020 • Yuan Yao, Nico Schertler, Enrique Rosales, Helge Rhodin, Leonid Sigal, Alla Sheffer
Reconstruction of a 3D shape from a single 2D image is a classical computer vision problem, whose difficulty stems from the inherent ambiguity of recovering occluded or only partially observed surfaces.
no code implementations • 10 Dec 2019 • Sam Likun Xi, Yuan YAO, Kshitij Bhardwaj, Paul Whatmough, Gu-Yeon Wei, David Brooks
In recent years, there has been tremendous advances in hardware acceleration of deep neural networks.
no code implementations • 1 Dec 2019 • Ke Ma, Jinshan Zeng, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan YAO
Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years.
1 code implementation • 5 Nov 2019 • Yuan Yao, Haoxi Zhong, Zhengyan Zhang, Xu Han, Xiaozhi Wang, Chaojun Xiao, Guoyang Zeng, Zhiyuan Liu, Maosong Sun
In this work, we propose a challenging adversarial language game called Adversarial Taboo as an example, in which an attacker and a defender compete around a target word.
1 code implementation • IJCNLP 2019 • Ruidong Wu, Yuan YAO, Xu Han, Ruobing Xie, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun
Open relation extraction (OpenRE) aims to extract relational facts from the open-domain corpus.
1 code implementation • NeurIPS 2019 • Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan YAO
In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective.
no code implementations • 5 Oct 2019 • Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan YAO, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou
Based on this framework, we demonstrate that SGLD can prevent the information leakage of the training dataset to a certain extent.
1 code implementation • IJCNLP 2019 • Xu Han, Tianyu Gao, Yuan YAO, Demin Ye, Zhiyuan Liu, Maosong Sun
OpenNRE is an open-source and extensible toolkit that provides a unified framework to implement neural models for relation extraction (RE).
no code implementations • 25 Sep 2019 • Zuyuan Zhong, Chen Liu, Yanwei Fu, Yuan YAO
Network structures are important to learning good representations of many tasks in computer vision and machine learning communities.
no code implementations • 25 Sep 2019 • Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan YAO
Over-parameterization is ubiquitous nowadays in training neural networks to benefit both optimization in seeking global optima and generalization in reducing prediction error.
no code implementations • 9 Sep 2019 • Jinlin Liu, Yuan YAO, Jianqiang Ren
The proposed acceleration framework makes it possible to generate high resolution images using less training time with limited hardware resource.
no code implementations • 28 Aug 2019 • Yuan Yao, Yu Zhang, Xutao Li, Yunming Ye
Heterogeneous domain adaptation (HDA) aims to facilitate the learning task in a target domain by borrowing knowledge from a heterogeneous source domain.
4 code implementations • ACL 2019 • Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zheng-Hao Liu, Zhiyuan Liu, Lixin Huang, Jie zhou, Maosong Sun
Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs.
Ranked #59 on Relation Extraction on DocRED
1 code implementation • 23 May 2019 • Yanwei Fu, Chen Liu, Donghao Li, Zuyuan Zhong, Xinwei Sun, Jinshan Zeng, Yuan YAO
To fill in this gap, this paper proposes a new approach based on differential inclusions of inverse scale spaces, which generate a family of models from simple to complex ones along the dynamics via coupling a pair of parameters, such that over-parameterized deep models and their structural sparsity can be explored simultaneously.
no code implementations • ICLR 2019 • Yifei HUANG, Yuan YAO, Weizhi Zhu
A belief persists long in machine learning that enlargement of margins over training data accounts for the resistance of models to overfitting by increasing the robustness.
no code implementations • ICLR 2019 • Yanwei Fu, Shun Zhang, Donghao Li, Xinwei Sun, xiangyang xue, Yuan YAO
This paper proposes a Pruning in Training (PiT) framework of learning to reduce the parameter size of networks.
no code implementations • ICLR 2019 • Chao GAO, jiyi LIU, Yuan YAO, Weizhi Zhu
In particular, we show that a JS-GAN that uses a neural network discriminator with at least one hidden layer is able to achieve the minimax rate of robust mean estimation under Huber's $\epsilon$-contamination model.
no code implementations • 24 Apr 2019 • Yanwei Fu, Donghao Li, Xinwei Sun, Shun Zhang, Yizhou Wang, Yuan YAO
This paper proposes a novel Stochastic Split Linearized Bregman Iteration ($S^{2}$-LBI) algorithm to efficiently train the deep network.
no code implementations • CVPR 2019 • Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang, Yuan YAO
The problem of estimating subjective visual properties (SVP) of images (e. g., Shoes A is more comfortable than B) is gaining rising attention.
1 code implementation • 5 Mar 2019 • Chao Gao, Yuan YAO, Weizhi Zhu
Robust scatter estimation is a fundamental task in statistics.
1 code implementation • 10 Feb 2019 • Min Zhou, Mingwei Dai, Yuan YAO, Jin Liu, Can Yang, Heng Peng
In this paper, we first propose a simple method for sure screening interactions (SSI).
Methodology
1 code implementation • 6 Feb 2019 • Jinshan Zeng, Shao-Bo Lin, Yuan YAO, Ding-Xuan Zhou
In this paper, we develop an alternating direction method of multipliers (ADMM) for deep neural networks training with sigmoid-type activation functions (called \textit{sigmoid-ADMM pair}), mainly motivated by the gradient-free nature of ADMM in avoiding the saturation of sigmoid-type activations and the advantages of deep neural networks with sigmoid-type activations (called deep sigmoid nets) over their rectified linear unit (ReLU) counterparts (called deep ReLU nets) in terms of approximation.
1 code implementation • CVPR 2019 • Yuan Yao, Jianqiang Ren, Xuansong Xie, Weidong Liu, Yong-Jin Liu, Jun Wang
Neural style transfer has drawn considerable attention from both academic and industrial field.
no code implementations • 4 Dec 2018 • Yuan Yao, Hyun Soo Park
We hypothesize that it is possible to leverage multiview image streams that are linked through the underlying 3D geometry, which can provide an additional supervisionary signal to train a segmentation model.
1 code implementation • EMNLP 2018 • Xu Han, Hao Zhu, Pengfei Yu, ZiYun Wang, Yuan YAO, Zhiyuan Liu, Maosong Sun
The relation of each sentence is first recognized by distant supervision methods, and then filtered by crowdworkers.
1 code implementation • 20 Oct 2018 • Yin Xian, Hanlin Gu, Wei Wang, Xuhui Huang, Yuan YAO, Yang Wang, Jian-Feng Cai
We introduce the use of data-driven tight frame (DDTF) algorithm for cryo-EM image denoising.
Computation Image and Video Processing
no code implementations • 8 Oct 2018 • Chendi Huang, Yuan YAO
Sparse model selection is ubiquitous from linear regression to graphical models where regularization paths, as a family of estimators upon the regularization parameter varying, are computed when the regularization parameter is unknown or decided data-adaptively.
1 code implementation • 8 Oct 2018 • Weizhi Zhu, Yifei HUANG, Yuan YAO
In this paper, we revisit Breiman's dilemma in deep neural networks with recently proposed spectrally normalized margins, from a novel perspective based on phase transitions of normalized margin distributions in training dynamics.
2 code implementations • 4 Oct 2018 • Chao Gao, jiyi LIU, Yuan YAO, Weizhi Zhu
Similar to the derivation of $f$-GANs, we show that these depth functions that lead to statistically optimal robust estimators can all be viewed as variational lower bounds of the total variation distance in the framework of $f$-Learning.
no code implementations • 29 Jul 2018 • Qianqian Xu, Jiechao Xiong, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan YAO
A preference order or ranking aggregated from pairwise comparison data is commonly understood as a strict total order.
no code implementations • ICML 2018 • Bo Zhao, Xinwei Sun, Yanwei Fu, Yuan YAO, Yizhou Wang
To solve this task, $L_{1}$ regularization is widely used for the pursuit of feature selection and avoiding overfitting, and yet the sparse estimation of features in $L_{1}$ regularization may cause the underfitting of training data.
1 code implementation • ICCV 2019 • Yuan Yao, Yasamin Jafarian, Hyun Soo Park
While multiview geometry can be used to self-supervise the unlabeled data, integrating the geometry into learning a keypoint detector is challenging due to representation mismatch.
no code implementations • 24 Mar 2018 • Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao
Training deep neural networks (DNNs) efficiently is a challenge due to the associated highly nonconvex optimization.
no code implementations • 8 Mar 2018 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan YAO
In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or social utility function which generates their comparison behaviors in experiments.
2 code implementations • 1 Mar 2018 • Jinshan Zeng, Tim Tsz-Kit Lau, Shao-Bo Lin, Yuan YAO
Deep learning has aroused extensive attention due to its great empirical success.
no code implementations • 20 Nov 2017 • Bo Zhao, Xinwei Sun, Yuan YAO, Yizhou Wang
With the learned SRG, each unseen class prototype (cluster center) in the image feature space can be synthesized by the linear combination of other class prototypes, so that testing instances can be classified based on the distance to these synthesized prototypes.
1 code implementation • 17 Nov 2017 • Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan YAO
Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years.
no code implementations • 16 Nov 2017 • Qianqian Xu, Jiechao Xiong, Xi Chen, Qingming Huang, Yuan YAO
Recently, crowdsourcing has emerged as an effective paradigm for human-powered large scale problem solving in various domains.
no code implementations • 15 Oct 2017 • Tsz Kit Lau, Yuan YAO
Nonconvex optimization problems arise in different research fields and arouse lots of attention in signal processing, statistics and machine learning.
no code implementations • 18 Jul 2017 • Qianqian Xu, Ming Yan, Chendi Huang, Jiechao Xiong, Qingming Huang, Yuan YAO
Outlier detection is a crucial part of robust evaluation for crowdsourceable assessment of Quality of Experience (QoE) and has attracted much attention in recent years.
5 code implementations • 2 May 2017 • Jing Liao, Yuan YAO, Lu Yuan, Gang Hua, Sing Bing Kang
We propose a new technique for visual attribute transfer across images that may have very different appearance but have perceptually similar semantic structure.
no code implementations • 16 Apr 2017 • Chendi Huang, Xinwei Sun, Jiechao Xiong, Yuan YAO
Boosting as gradient descent algorithms is one popular method in machine learning.
no code implementations • NeurIPS 2016 • Chendi Huang, Xinwei Sun, Jiechao Xiong, Yuan YAO
An iterative regularization path with structural sparsity is proposed in this paper based on variable splitting and the Linearized Bregman Iteration, hence called \emph{Split LBI}.
no code implementations • 12 Jul 2016 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan YAO
In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or utility function which generates their comparison behaviors in experiments.
no code implementations • 19 May 2016 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan YAO
With the rapid growth of crowdsourcing platforms it has become easy and relatively inexpensive to collect a dataset labeled by multiple annotators in a short time.
no code implementations • 28 Feb 2015 • Braxton Osting, Jiechao Xiong, Qianqian Xu, Yuan YAO
In this setting, a pairwise comparison dataset is typically gathered via random sampling, either \emph{with} or \emph{without} replacement.
no code implementations • 25 Jan 2015 • Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Jiechao Xiong, Shaogang Gong, Yizhou Wang, Yuan YAO
In this paper, we propose a more principled way to identify annotation outliers by formulating the subjective visual property prediction task as a unified robust learning to rank problem, tackling both the outlier detection and learning to rank jointly.
no code implementations • 15 Aug 2014 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan YAO
In this paper we study the problem of how to estimate such visual properties from a ranking perspective with the help of the annotators from online crowdsourcing platforms.
no code implementations • 2 Jul 2014 • Haixia Liu, Raymond H. Chan, Yuan YAO
Then a forward stage-wise rank boosting is used to select a small set of features for more accurate classification so that van Gogh paintings are highly concentrated towards some center point while forgeries are spread out as outliers.
1 code implementation • 30 Jun 2014 • Stanley Osher, Feng Ruan, Jiechao Xiong, Yuan YAO, Wotao Yin
In this paper, we recover sparse signals from their noisy linear measurements by solving nonlinear differential inclusions, which is based on the notion of inverse scale space (ISS) developed in applied mathematics.
no code implementations • 27 Nov 2013 • Yuan Yao, Hanghang Tong, Tao Xie, Leman Akoglu, Feng Xu, Jian Lu
Community Question Answering (CQA) websites have become valuable repositories which host a massive volume of human knowledge.