1 code implementation • ACL 2022 • Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang
However, the imbalanced training dataset leads to poor performance on rare senses and zero-shot senses.
1 code implementation • COLING 2022 • Kaixin Wu, Yue Zhang, Bojie Hu, Tong Zhang
Extensive experiments on ten WMT machine translation tasks show that the proposed model yields an average of 1. 35x faster (with almost no decrease in BLEU) over the state-of-the-art inference implementation.
no code implementations • NLP4ConvAI (ACL) 2022 • Tong Zhang, Yong liu, Boyang Li, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao
Conversational Recommendation Systems recommend items through language based interactions with users. In order to generate naturalistic conversations and effectively utilize knowledge graphs (KGs) containing background information, we propose a novel Bag-of-Entities loss, which encourages the generated utterances to mention concepts related to the item being recommended, such as the genre or director of a movie.
no code implementations • 30 May 2024 • Ke Yi, Yuhui Xu, Heng Chang, Chen Tang, Yuan Meng, Tong Zhang, Jia Li
Large Language Models (LLMs) have advanced rapidly but face significant memory demands.
no code implementations • 27 May 2024 • Haohan Weng, Yikai Wang, Tong Zhang, C. L. Philip Chen, Jun Zhu
Generating compact and sharply detailed 3D meshes poses a significant challenge for current 3D generative models.
no code implementations • 27 May 2024 • Xunpeng Huang, Difan Zou, Yi-An Ma, Hanze Dong, Tong Zhang
Stochastic gradients have been widely integrated into Langevin-based methods to improve their scalability and efficiency in solving large-scale sampling problems.
no code implementations • 26 May 2024 • Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yi-An Ma, Tong Zhang
To generate data from trained diffusion models, most inference algorithms, such as DDPM, DDIM, and other variants, rely on discretizing the reverse SDEs or their equivalent ODEs.
no code implementations • 22 May 2024 • Licheng Shen, Ho Ngai Chow, Lingyun Wang, Tong Zhang, Mengqiu Wang, Yuxing Han
In this paper, we present Gaussian Time Machine (GTM) which models the time-dependent attributes of Gaussian primitives with discrete time embedding vectors decoded by a lightweight Multi-Layer-Perceptron(MLP).
1 code implementation • 20 May 2024 • Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, dingnan jin, Hongru Liang, Tat-Seng Chua
To this end, we introduce CLAMBER, a benchmark for evaluating LLMs using a well-organized taxonomy.
no code implementations • 17 May 2024 • Cheng Niu, Xingguang Wang, Xuxin Cheng, Juntong Song, Tong Zhang
Then a two-stage fine-tuning on LLaMA 2 is performed on the generated data and the real data for the DST prediction.
2 code implementations • 13 May 2024 • Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
We present the workflow of Online Iterative Reinforcement Learning from Human Feedback (RLHF) in this technical report, which is widely reported to outperform its offline counterpart by a large margin in the recent large language model (LLM) literature.
no code implementations • 23 Apr 2024 • Tong Zhang, Wenxue Cui, Shaohui Liu, Feng Jiang
Convolutional Neural Network (CNN) and Transformer have attracted much attention recently for video post-processing (VPP).
no code implementations • 11 Apr 2024 • Yanhao Wu, Tong Zhang, Wei Ke, Congpei Qiu, Sabine Susstrunk, Mathieu Salzmann
Subsequently, we introduce a context-aware feature learning strategy, which encodes object patterns without relying on their specific context by aggregating object features across various scenes.
no code implementations • 4 Apr 2024 • Miao Lu, Han Zhong, Tong Zhang, Jose Blanchet
Unlike previous work, which relies on a generative model or a pre-collected offline dataset enjoying good coverage of the deployment environment, we tackle robust RL via interactive data collection, where the learner interacts with the training environment only and refines the policy through trial and error.
no code implementations • 2 Apr 2024 • Zixuan Zhang, Revanth Gangi Reddy, Kevin Small, Tong Zhang, Heng Ji
In addition, it is still unclear how well an OpenQA model can transfer to completely new knowledge domains.
no code implementations • 26 Mar 2024 • Yifan Hao, Yong Lin, Difan Zou, Tong Zhang
We demonstrate that in this scenario, further increasing the model's parameterization can significantly reduce the OOD loss.
1 code implementation • 26 Mar 2024 • Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang
Attempting to complement this deficiency, we investigate the layerwise properties of LoRA on fine-tuning tasks and observe an unexpected but consistent skewness of weight norms across different layers.
1 code implementation • 20 Mar 2024 • Chen Zhao, Tong Zhang, Zheng Dang, Mathieu Salzmann
Determining the relative pose of an object between two images is pivotal to the success of generalizable object pose estimation.
no code implementations • 18 Mar 2024 • Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
The performance drops from the common to counter groups quantify the reliance of models on spurious features (i. e., backgrounds) to predict the animals.
no code implementations • 15 Mar 2024 • Yongjie Wang, Tong Zhang, Xu Guo, Zhiqi Shen
Due to the lack of a rigorous definition of explainable AI (XAI), a plethora of research related to explainability, interpretability, and transparency has been developed to explain and analyze the model from various perspectives.
no code implementations • 14 Mar 2024 • Haohan Weng, Danqing Huang, Yu Qiao, Zheng Hu, Chin-Yew Lin, Tong Zhang, C. L. Philip Chen
In this paper, we present Desigen, an automatic template creation pipeline which generates background images as well as harmonious layout elements over the background.
no code implementations • 13 Mar 2024 • ZiCheng Zhang, Tong Zhang, Yi Zhu, Jianzhuang Liu, Xiaodan Liang, Qixiang Ye, Wei Ke
To mitigate these issues, we propose a Language-Driven Visual Consensus (LDVC) approach, fostering improved alignment of semantic and visual information. Specifically, we leverage class embeddings as anchors due to their discrete and abstract nature, steering vision features toward class embeddings.
no code implementations • 13 Mar 2024 • Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang
To mitigate this issue, we propose Bootstrapped Preference Optimization (BPO), which conducts preference learning with datasets containing negative responses bootstrapped from the model itself.
Ranked #32 on Visual Question Answering on MM-Vet
no code implementations • 11 Mar 2024 • Baran Ozaydin, Tong Zhang, Deblina Bhattacharjee, Sabine Süsstrunk, Mathieu Salzmann
Our OMH yields better unsupervised segmentation performance compared to existing USS methods.
no code implementations • 11 Mar 2024 • Tong Zhang, Chen Huang, Yang Deng, Hongru Liang, Jia Liu, Zujie Wen, Wenqiang Lei, Tat-Seng Chua
We investigate non-collaborative dialogue agents, which are expected to engage in strategic conversations with diverse users, for securing a mutual agreement that leans favorably towards the system's objectives.
no code implementations • 10 Mar 2024 • Xunpeng Huang, Hanze Dong, Difan Zou, Tong Zhang
Along this line, Freund et al. (2022) suggest that the modified Langevin algorithm with prior diffusion is able to converge dimension independently for strongly log-concave target distributions.
no code implementations • 6 Mar 2024 • Wei zhang, Miaoxin Cai, Tong Zhang, Guoqiang Lei, Yin Zhuang, Xuerui Mao
Ship detection needs to identify ship locations from remote sensing (RS) scenes.
no code implementations • 29 Feb 2024 • Xiang Chen, Wenjie Zhu, Jiayuan Chen, Tong Zhang, Changyan Yi, Jun Cai
This paper proposes a novel edge computing enabled real-time video analysis system for intelligent visual devices.
1 code implementation • 28 Feb 2024 • Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
Additionally, DPA models user preferences as directions (i. e., unit vectors) in the reward space to achieve user-dependent preference control.
no code implementations • 15 Feb 2024 • Ying Su, Tianqing Fang, Huiru Xiao, Weiqi Wang, Yangqiu Song, Tong Zhang, Lei Chen
In this paper, we propose to adopt textual entailment to find implicit entailment relations between CSKG nodes, to effectively densify the subgraph connecting nodes within the same conceptual class, which indicates a similar level of plausibility.
no code implementations • 14 Feb 2024 • Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang
We also prove a lower bound to show that the additive dependence on $C$ is optimal.
Model-based Reinforcement Learning reinforcement-learning +1
no code implementations • 11 Feb 2024 • Chenlu Ye, Wei Xiong, Yuheng Zhang, Nan Jiang, Tong Zhang
We study Reinforcement Learning from Human Feedback (RLHF) under a general preference oracle.
1 code implementation • 6 Feb 2024 • Tianyang Han, Qing Lian, Rui Pan, Renjie Pi, Jipeng Zhang, Shizhe Diao, Yong Lin, Tong Zhang
In this paper, we identify a typical class of inputs that baffles MLLMs, which consist of images that are highly relevant but inconsistent with answers, causing MLLMs to suffer from hallucination.
1 code implementation • 31 Jan 2024 • Ying Su, Jipeng Zhang, Yangqiu Song, Tong Zhang
To facilitate the evaluation of pruned subgraphs, we also propose a graph attention network (GAT) based module to reason with the subgraph data.
1 code implementation • 30 Jan 2024 • Wei zhang, Miaoxin Cai, Tong Zhang, Yin Zhuang, Xuerui Mao
Multi-modal large language models (MLLMs) have demonstrated remarkable success in vision and visual-language tasks within the natural image domain.
no code implementations • 21 Jan 2024 • Chengbo Yuan, Chuan Wen, Tong Zhang, Yang Gao
Our predicted flow offers actionable geometric and physics guidance, thus facilitating stable zero-shot skill transfer in real-world scenarios. We deploy our method with a policy based on closed-loop flow prediction.
no code implementations • 19 Jan 2024 • Yifan Hao, Tong Zhang
Recent empirical and theoretical studies have established the generalization capabilities of large machine learning models that are trained to (approximately or exactly) fit noisy data.
no code implementations • 12 Jan 2024 • Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang
Specifically, DMC follows the reverse SDE of a diffusion process that transforms the target distribution to the standard Gaussian, utilizing a non-parametric score estimation.
1 code implementation • 5 Jan 2024 • Renjie Pi, Tianyang Han, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang
The deployment of multimodal large language models (MLLMs) has brought forth a unique vulnerability: susceptibility to malicious attacks through visual inputs.
no code implementations • 3 Jan 2024 • Ernest Perkowski, Rui Pan, Tuan Dung Nguyen, Yuan-Sen Ting, Sandor Kruk, Tong Zhang, Charlie O'Neill, Maja Jablonska, Zechang Sun, Michael J. Smith, Huiling Liu, Kevin Schawinski, Kartheik Iyer, Ioana Ciucă for UniverseTBD
We explore the potential of enhancing LLM performance in astronomy-focused question-answering through targeted, continual pre-training.
1 code implementation • 31 Dec 2023 • Cheng Niu, Yuanhao Wu, Juno Zhu, Siliang Xu, Kashun Shum, Randy Zhong, Juntong Song, Tong Zhang
Retrieval-augmented generation (RAG) has become a main technique for alleviating hallucinations in large language models (LLMs).
no code implementations • 22 Dec 2023 • Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang
This means SGD with heavy-ball momentum is useful in the large-batch settings such as distributed machine learning or federated learning, where a smaller number of iterations can significantly reduce the number of communication rounds, leading to acceleration in practice.
3 code implementations • 18 Dec 2023 • Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang
We investigate its behavior in three distinct settings -- offline, online, and hybrid -- and propose efficient algorithms with finite-sample theoretical guarantees.
1 code implementation • 14 Dec 2023 • Jiaqi Tang, Hao Lu, Xiaogang Xu, Ruizheng Wu, Sixing Hu, Tong Zhang, Tsz Wa Cheng, Ming Ge, Ying-Cong Chen, Fugee Tsung
Artificial Intelligence (AI)-driven defect inspection is pivotal in industrial manufacturing.
no code implementations • 7 Dec 2023 • Shibin Wu, Bang Yang, Zhiyu Ye, Haoqian Wang, Hairong Zheng, Tong Zhang
Medical report generation demands automatic creation of coherent and precise descriptions for medical images.
no code implementations • 5 Dec 2023 • Zhi Chen, Yufan Ren, Tong Zhang, Zheng Dang, Wenbing Tao, Sabine Süsstrunk, Mathieu Salzmann
We propose formulating PCR as a denoising diffusion probabilistic process, mapping noisy transformations to the ground truth.
no code implementations • 29 Nov 2023 • Yingdong Hu, Fanqi Lin, Tong Zhang, Li Yi, Yang Gao
In this study, we are interested in imbuing robots with the capability of physically-grounded task planning.
no code implementations • 27 Nov 2023 • Tong Zhang, Haoyang Liu, Peiyan Zhang, Yuxuan Cheng, Haohan Wang
Our method focuses on producing SVGs that are both accurate and simple, aligning with human readability and understanding.
1 code implementation • 16 Nov 2023 • Hanning Zhang, Shizhe Diao, Yong Lin, Yi R. Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang
This approach is formalized by first identifying the disparity in knowledge encompassed by pre-trained parameters compared to that of instruction tuning data.
1 code implementation • 14 Nov 2023 • Rui Pan, Shuo Xing, Shizhe Diao, Wenhe Sun, Xiang Liu, Kashun Shum, Renjie Pi, Jipeng Zhang, Tong Zhang
Since the emergence of large language models, prompt learning has become a popular method for optimizing and customizing these models.
1 code implementation • 11 Nov 2023 • Haoyu Ma, Tong Zhang, Shanlin Sun, Xiangyi Yan, Kun Han, Xiaohui Xie
Reconstructing personalized animatable head avatars has significant implications in the fields of AR/VR.
no code implementations • 11 Nov 2023 • Renjie Pi, Lewei Yao, Jiahui Gao, Jipeng Zhang, Tong Zhang
In this paper, we present a novel end-to-end framework named PerceptionGPT, which efficiently and effectively equips the VLLMs with visual perception abilities by leveraging the representation power of LLMs' token embedding.
no code implementations • 6 Nov 2023 • Ehsan Pajouheshgar, Yitao Xu, Alexander Mordvintsev, Eyvind Niklasson, Tong Zhang, Sabine Süsstrunk
We propose Mesh Neural Cellular Automata (MeshNCA), a method that directly synthesizes dynamic textures on 3D meshes without requiring any UV maps.
1 code implementation • NeurIPS 2023 • Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang
Notably, under the assumption of single policy coverage and the knowledge of $\zeta$, our proposed algorithm achieves a suboptimality bound that is worsened by an additive factor of $\mathcal{O}(\zeta (C(\widehat{\mathcal{F}},\mu)n)^{-1})$ due to the corruption.
2 code implementations • 19 Oct 2023 • Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
Offline reinforcement learning (RL) presents a promising approach for learning reinforced policies from offline datasets without the need for costly or unsafe interactions with the environment.
no code implementations • 12 Oct 2023 • Haohan Weng, Tianyu Yang, Jianan Wang, Yu Li, Tong Zhang, C. L. Philip Chen, Lei Zhang
Large image diffusion models enable novel view synthesis with high quality and excellent zero-shot capability.
no code implementations • 5 Oct 2023 • Chen Zhao, Tong Zhang, Mathieu Salzmann
Our goal then is to estimate the relative object pose between this reference view and a query image that depicts the object in a different pose.
no code implementations • 29 Sep 2023 • Yong Lin, Lu Tan, Yifan Hao, Honam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang
Contrary to the conventional wisdom that focuses on learning invariant features for better OOD performance, our findings suggest that incorporating a large number of diverse spurious features weakens their individual contributions, leading to improved overall OOD generalization performance.
no code implementations • 25 Sep 2023 • Tong Zhang, X. Jessie Yang, Boyang Li
With this paper, we investigate if free-form conversations can enhance users' comprehension of static explanations, improve acceptance and trust in the explanation methods, and facilitate human-AI collaboration.
1 code implementation • 18 Sep 2023 • Helbert Paat, Qing Lian, Weilong Yao, Tong Zhang
In this paper, we present the first approach that addresses the inherent ambiguities present in pseudo labels by introducing an Evidential Deep Learning (EDL) based uncertainty estimation framework.
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.
1 code implementation • 11 Sep 2023 • Yide Qiu, Shaoxiang Ling, Tong Zhang, Bo Huang, Zhen Cui
To perform effective learning on the large-scale UniKG, two key measures are taken, including (i) the semantic alignment strategy for multi-attribute entities, which projects the feature description of multi-attribute nodes into a common embedding space to facilitate node aggregation in a large receptive field; (ii) proposing a novel plug-and-play anisotropy propagation module (APM) to learn effective multi-hop anisotropy propagation kernels, which extends methods of large-scale homogeneous graphs to heterogeneous graphs.
no code implementations • 9 Sep 2023 • Menghao Hu, Tong Zhang, Shuai Wang, Guoliang Li, Yingyang Chen, Qiang Li, Gaojie Chen
Terrestrial robots, i. e., unmanned ground vehicles (UGVs), and aerial robots, i. e., unmanned aerial vehicles (UAVs), operate in separate spaces.
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 • 16 Aug 2023 • Jianyu Wen, Chenhao Wu, Tong Zhang, Yixuan Yu, Piotr Swierczynski
In this paper, we propose a 2-stage low-light image enhancement method called Self-Reference Deep Adaptive Curve Estimation (Self-DACE).
no code implementations • 10 Jul 2023 • Aixuan Li, Jing Zhang, Yunqiu Lv, Tong Zhang, Yiran Zhong, Mingyi He, Yuchao Dai
In this case, salient objects are typically non-camouflaged, and camouflaged objects are usually not salient.
no code implementations • 5 Jul 2023 • Xunpeng Huang, Hanze Dong, Yifan Hao, Yi-An Ma, Tong Zhang
We propose a Monte Carlo sampler from the reverse diffusion process.
1 code implementation • 21 Jun 2023 • Shizhe Diao, Rui Pan, Hanze Dong, Ka Shun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
As the number of available foundation models and specialized tasks keeps growing, the job of training scientific language models becomes highly nontrivial.
no code implementations • 18 Jun 2023 • Tong Zhang, Yingdong Hu, Hanchen Cui, Hang Zhao, Yang Gao
To this end, we present $\textbf{Semantic-Geometric Representation} (\textbf{SGR})$, a universal perception module for robotics that leverages the rich semantic information of large-scale pre-trained 2D models and inherits the merits of 3D spatial reasoning.
1 code implementation • 18 Jun 2023 • Yifan Zhao, Tong Zhang, Jia Li, Yonghong Tian
Recent progress in this setting assumes that the base knowledge and novel query samples are distributed in the same domains, which are usually infeasible for realistic applications.
no code implementations • 18 Jun 2023 • Guangbu Liu, Tong Zhang, Xudong Wang, Wenting Zhao, Chuanwei Zhou, Zhen Cui
Instead of a plain use of a base graph dictionary, we propose the variational graph dictionary adaptation (VGDA) to generate a personalized dictionary (named adapted graph dictionary) for catering to each input graph.
no code implementations • 9 Jun 2023 • Bang Yang, Asif Raza, Yuexian Zou, Tong Zhang
In this work, we propose customizing off-the-shelf general-purpose large-scale pre-trained models, i. e., foundation models (FMs), in computer vision and natural language processing with a specific focus on medical report generation.
1 code implementation • 8 Jun 2023 • Shizhe Diao, Tianyang Xu, Ruijia Xu, Jiawei Wang, Tong Zhang
Pre-trained language models (PLMs) demonstrate excellent abilities to understand texts in the generic domain while struggling in a specific domain.
1 code implementation • 30 May 2023 • Rui Yang, Yong Lin, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang
In this paper, we study out-of-distribution (OOD) generalization of offline GCRL both theoretically and empirically to identify factors that are important.
no code implementations • 24 May 2023 • Dongqing Wang, Tong Zhang, Alaa Abboud, Sabine Süsstrunk
We propose InNeRF360, an automatic system that accurately removes text-specified objects from 360-degree Neural Radiance Fields (NeRF).
1 code implementation • 23 May 2023 • Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang
Overall, our proposed paradigm and DetGPT demonstrate the potential for more sophisticated and intuitive interactions between humans and machines.
no code implementations • 22 May 2023 • Xiaoyu Wang, Rui Pan, Renjie Pi, Tong Zhang
To address this issue, we propose a reformulation of bilevel optimization as a minimax problem, effectively decoupling the outer-inner dependency.
no code implementations • 12 May 2023 • Haiqi Liu, C. L. Philip Chen, Xinrong Gong, Tong Zhang
Recognizing novel sub-categories with scarce samples is an essential and challenging research topic in computer vision.
1 code implementation • 18 Apr 2023 • Wentao Zhang, Yujun Huang, Tong Zhang, Qingsong Zou, Wei-Shi Zheng, Ruixuan Wang
In particular, updating an intelligent diagnosis system with training data of new diseases would cause catastrophic forgetting of old disease knowledge.
no code implementations • 15 Apr 2023 • Tong Zhang, Wenxue Cui, Chen Hui, Feng Jiang
Deep network-based image and video Compressive Sensing(CS) has attracted increasing attentions in recent years.
3 code implementations • 13 Apr 2023 • Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
Utilizing a reward model and a sufficient number of samples, our approach selects the high-quality samples, discarding those that exhibit undesired behavior, and subsequently enhancing the model by fine-tuning on these filtered samples.
no code implementations • 12 Apr 2023 • Shiwei Zhang, Zhengzheng Wang, Qing Liu, Fei Wang, Wei Ke, Tong Zhang
This paper presents a new annotation method called Sparse Annotation (SA) for crowd counting, which reduces human labeling efforts by sparsely labeling individuals in an image.
no code implementations • 1 Apr 2023 • Chunyu Lei, C. L. Philip Chen, Jifeng Guo, Tong Zhang
Third, the TSMS feature fusion layer is proposed to extract more effective multi-scale features through the integration of CF layers and CE layers.
no code implementations • 29 Mar 2023 • Congpei Qiu, Tong Zhang, Wei Ke, Mathieu Salzmann, Sabine Süsstrunk
Dense Self-Supervised Learning (SSL) methods address the limitations of using image-level feature representations when handling images with multiple objects.
1 code implementation • CVPR 2023 • Yanhao Wu, Tong Zhang, Wei Ke, Sabine Süsstrunk, Mathieu Salzmann
In this paper, we introduce an SSL strategy that leverages positive pairs in both the spatial and temporal domain.
no code implementations • ICCV 2023 • Dongqing Wang, Tong Zhang, Sabine Süsstrunk
We propose NEMTO, the first end-to-end neural rendering pipeline to model 3D transparent objects with complex geometry and unknown indices of refraction.
no code implementations • 6 Mar 2023 • Jianqing Fan, Cong Fang, Yihong Gu, Tong Zhang
To the best of our knowledge, this paper is the first to realize statistically efficient invariance learning in the general linear model.
no code implementations • 2 Mar 2023 • Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang
To circumvent this difficulty, we examine the problem of identifying a mixed Nash equilibrium, where strategies are randomized and characterized by probability distributions over continuous domains. To this end, we propose PArticle-based Primal-dual ALgorithm (PAPAL) tailored for a weakly entropy-regularized min-max optimization over probability distributions.
2 code implementations • 24 Feb 2023 • Kashun Shum, Shizhe Diao, Tong Zhang
However, most CoT studies rely on carefully designed human-annotated rational chains to prompt LLMs, posing challenges for real-world applications where labeled data is available without rational chains.
2 code implementations • 23 Feb 2023 • Shizhe Diao, Pengcheng Wang, Yong Lin, Tong Zhang
For this purpose, we propose a solution to the key problem of determining which questions are the most important and helpful ones to annotate from a pool of task-specific queries.
no code implementations • 21 Feb 2023 • Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
We propose a variance-adaptive algorithm for linear mixture MDPs, which achieves a problem-dependent horizon-free regret bound that can gracefully reduce to a nearly constant regret for deterministic MDPs.
1 code implementation • 20 Feb 2023 • Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang
Social media classification tasks (e. g., tweet sentiment analysis, tweet stance detection) are challenging because social media posts are typically short, informal, and ambiguous.
no code implementations • 6 Feb 2023 • Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
Federated Averaging (FedAvg) and its variants are the most popular optimization algorithms in federated learning (FL).
no code implementations • 2 Feb 2023 • Tong Zhang, Yong liu, Boyang Li, Zhiwei Zeng, Pengwei Wang, Yuan You, Chunyan Miao, Lizhen Cui
HAHT maintains a long-term memory of history conversations and utilizes history information to understand current conversation context and generate well-informed and context-relevant responses.
1 code implementation • 1 Feb 2023 • Bu Jin, Xinyu Liu, Yupeng Zheng, Pengfei Li, Hao Zhao, Tong Zhang, Yuhang Zheng, Guyue Zhou, Jingjing Liu
To bridge the gap, we propose an end-to-end transformer-based architecture, ADAPT (Action-aware Driving cAPtion Transformer), which provides user-friendly natural language narrations and reasoning for each decision making step of autonomous vehicular control and action.
no code implementations • 31 Jan 2023 • Jonathan N. Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
POMDPs capture a broad class of decision making problems, but hardness results suggest that learning is intractable even in simple settings due to the inherent partial observability.
1 code implementation • 24 Jan 2023 • Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang
The overfitting issue is addressed by considering a bilevel formulation to search for the sample reweighting, in which the generalization complexity depends on the search space of sample weights instead of the model size.
no code implementations • 24 Jan 2023 • Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Tong Zhang
The goal of coreset selection in supervised learning is to produce a weighted subset of data, so that training only on the subset achieves similar performance as training on the entire dataset.
1 code implementation • 5 Jan 2023 • Bahar Aydemir, Ludo Hoffstetter, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk
Deep saliency prediction algorithms complement the object recognition features, they typically rely on additional information, such as scene context, semantic relationships, gaze direction, and object dissimilarity.
1 code implementation • CVPR 2023 • Bahar Aydemir, Ludo Hoffstetter, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk
Deep saliency prediction algorithms complement the object recognition features, they typically rely on additional information such as scene context, semantic relationships, gaze direction, and object dissimilarity.
Ranked #1 on Saliency Prediction on SALICON
no code implementations • 26 Dec 2022 • Baran Ozaydin, Tong Zhang, Sabine Süsstrunk, Mathieu Salzmann
To stylize the source content with the exemplar style, we extract unsupervised cross-domain semantic correspondences and warp the exemplar style to the source content.
1 code implementation • CVPR 2023 • Yufan Ren, Fangjinhua Wang, Tong Zhang, Marc Pollefeys, Sabine Süsstrunk
The success of the Neural Radiance Fields (NeRF) in novel view synthesis has inspired researchers to propose neural implicit scene reconstruction.
no code implementations • 12 Dec 2022 • Alekh Agarwal, Yujia Jin, Tong Zhang
We study time-inhomogeneous episodic reinforcement learning (RL) under general function approximation and sparse rewards.
no code implementations • 12 Dec 2022 • Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
In this paper, we consider the contextual bandit with general function approximation and propose a computationally efficient algorithm to achieve a regret of $\tilde{O}(\sqrt{T}+\zeta)$.
1 code implementation • 30 Nov 2022 • Rui Pan, Shizhe Diao, Jianlin Chen, Tong Zhang
In this paper, we present ExtremeBERT, a toolkit for accelerating and customizing BERT pretraining.
no code implementations • 29 Nov 2022 • Tong Zhang, Ying Tan, Xiang Chen, Zike Lei
The key design idea for this observer is to estimate the visible set and identify the mis-identified features from the measurements.
no code implementations • 25 Nov 2022 • Hanze Dong, Xi Wang, Yong Lin, Tong Zhang
With the popularity of Stein variational gradient descent (SVGD), the focus of particle-based VI algorithms has been on the properties of functions in Reproducing Kernel Hilbert Space (RKHS) to approximate the gradient flow.
1 code implementation • 21 Nov 2022 • Hanze Dong, Shizhe Diao, Weizhong Zhang, Tong Zhang
The resulting method is significantly more powerful than the standard normalization flow approach for generating data distributions with multiple modes.
no code implementations • CVPR 2023 • Ehsan Pajouheshgar, Yitao Xu, Tong Zhang, Sabine Süsstrunk
Current Dynamic Texture Synthesis (DyTS) models can synthesize realistic videos.
no code implementations • 20 Nov 2022 • Zhongyu Fang, Aoyun He, Qihui Yu, Baopeng Gao, Weiping Ding, Tong Zhang, Lei Ma
In this paper, we developed a large multimodal emotion dataset, named "HED" dataset, to facilitate the emotion recognition task, and accordingly propose a multimodal emotion recognition method.
no code implementations • 11 Nov 2022 • Kilean Hwang, Tomofumi Maruta, Alexander Plastun, Kei Fukushima, Tong Zhang, Qiang Zhao, Peter Ostroumov, Yue Hao
Bayesian optimization~(BO) is often used for accelerator tuning due to its high sample efficiency.
no code implementations • 3 Nov 2022 • Han Zhong, Wei Xiong, Sirui Zheng, LiWei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang
The proposed algorithm modifies the standard posterior sampling algorithm in two aspects: (i) we use an optimistic prior distribution that biases towards hypotheses with higher values and (ii) a loglikelihood function is set to be the empirical loss evaluated on the historical data, where the choice of loss function supports both model-free and model-based learning.
no code implementations • 18 Oct 2022 • Xinrao Li, Tong Zhang, Shuai Wang, Guangxu Zhu, Rui Wang, Tsung-Hui Chang
However, wireless channels between the edge server and the autonomous vehicles are time-varying due to the high-mobility of vehicles.
no code implementations • 16 Oct 2022 • Baijun Ji, Tong Zhang, Yicheng Zou, Bojie Hu, Si Shen
Multimodal machine translation (MMT) aims to improve translation quality by equipping the source sentence with its corresponding image.
1 code implementation • 14 Oct 2022 • Ying Su, ZiHao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song, Tong Zhang
Commonsense reasoning tasks such as commonsense knowledge graph completion and commonsense question answering require powerful representation learning.
1 code implementation • COLING 2022 • Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang
As a key natural language processing (NLP) task, word sense disambiguation (WSD) evaluates how well NLP models can understand the lexical semantics of words under specific contexts.
no code implementations • 4 Oct 2022 • Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
Existing studies on provably efficient algorithms for Markov games (MGs) almost exclusively build on the "optimism in the face of uncertainty" (OFU) principle.
no code implementations • 27 Sep 2022 • Tong Zhang, Christopher Williams, Reza Ahmadian, Meysam Qadrdan
It was demonstrated that by exploiting the flexibility offered by the tidal lagoon, it can achieve a higher revenue in the day-ahead market, although their total electricity generation is reduced.
no code implementations • 14 Sep 2022 • Xinwei Shen, Kani Chen, Tong Zhang
We show that for parametric generative models that are correctly specified, all $f$-divergence GANs with the same discriminator classes are asymptotically equivalent under suitable regularity conditions.
no code implementations • COLING 2022 • Zile Qiao, Wei Ye, Tong Zhang, Tong Mo, Weiping Li, Shikun Zhang
Answering natural language questions on knowledge graphs (KGQA) remains a great challenge in terms of understanding complex questions via multi-hop reasoning.
no code implementations • NeurIPS 2021 • Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
Thompson Sampling is one of the most effective methods for contextual bandits and has been generalized to posterior sampling for certain MDP settings.
1 code implementation • 12 Aug 2022 • Zhengcen Li, Yueran Li, Linlin Tang, Tong Zhang, Jingyong Su
To overcome the above shortcoming, we introduce a novel unified two-person graph to represent inter-body and intra-body correlations between joints.
no code implementations • 11 Aug 2022 • Jia-Xin Zhuang, Xiansong Huang, Yang Yang, Jiancong Chen, Yue Yu, Wei Gao, Ge Li, Jie Chen, Tong Zhang
In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelligence (AI) computing platforms.
1 code implementation • 8 Jul 2022 • Tong Zhang, Peng Gao, Hao Dong, Yin Zhuang, Guanqun Wang, Wei zhang, He Chen
Currently, under supervised learning, a model pretrained by a large-scale nature scene dataset and then fine-tuned on a few specific task labeling data is the paradigm that has dominated the knowledge transfer learning.
no code implementations • 21 Jun 2022 • Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi
Most prior results on differentially private stochastic gradient descent (DP-SGD) are derived under the simplistic assumption of uniform Lipschitzness, i. e., the per-sample gradients are uniformly bounded.
no code implementations • 15 Jun 2022 • Alekh Agarwal, Tong Zhang
We propose a general framework to design posterior sampling methods for model-based RL.
no code implementations • 9 Jun 2022 • Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang
Motivated by this observation, we propose a new quantity, average drift at optimum, to measure the effects of data heterogeneity, and explicitly use it to present a new theoretical analysis of FedAvg.
no code implementations • 9 Jun 2022 • Hao liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
Overparameterized neural networks enjoy great representation power on complex data, and more importantly yield sufficiently smooth output, which is crucial to their generalization and robustness.
no code implementations • 7 Jun 2022 • Yifei Sun, Jie Li, Tong Zhang, Rui Wang, Xiaohui Peng, Tony Xiao Han, Haisheng Tan
At the end, we show that the reconstructed room layout can be utilized to locate a mobile device according to its AoA spectrum, even with single access point.
no code implementations • 3 Jun 2022 • Yi-An Ma, Teodor Vanislavov Marinov, Tong Zhang
This paper considers the generalization performance of differentially private convex learning.
no code implementations • 31 May 2022 • Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, LiWei Wang, Tong Zhang
We also extend our techniques to the two-player zero-sum Markov games (MGs), and establish a new performance lower bound for MGs, which tightens the existing result, and verifies the nearly minimax optimality of the proposed algorithm.
no code implementations • CVPR 2022 • Deblina Bhattacharjee, Tong Zhang, Sabine Süsstrunk, Mathieu Salzmann
At the heart of our approach is a shared attention mechanism modeling the dependencies across the tasks.
no code implementations • 13 May 2022 • Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
We show that for both known $C$ and unknown $C$ cases, our algorithm with proper choice of hyperparameter achieves a regret that nearly matches the lower bounds.
no code implementations • 10 Apr 2022 • Hui Deng, Tong Zhang, Yuchao Dai, Jiawei Shi, Yiran Zhong, Hongdong Li
In this paper, we propose to model deep NRSfM from a sequence-to-sequence translation perspective, where the input 2D frame sequence is taken as a whole to reconstruct the deforming 3D non-rigid shape sequence.
no code implementations • CVPR 2022 • Tong Zhang, Congpei Qiu, Wei Ke, Sabine Süsstrunk, Mathieu Salzmann
In essence, this strategy ignores the fact that two crops may truly contain different image information, e. g., background and small objects, and thus tends to restrain the diversity of the learned representations.
no code implementations • 15 Mar 2022 • Alekh Agarwal, Tong Zhang
Provably sample-efficient Reinforcement Learning (RL) with rich observations and function approximation has witnessed tremendous recent progress, particularly when the underlying function approximators are linear.
1 code implementation • 8 Mar 2022 • Di Chang, Aljaž Božič, Tong Zhang, Qingsong Yan, Yingcong Chen, Sabine Süsstrunk, Matthias Nießner
Finding accurate correspondences among different views is the Achilles' heel of unsupervised Multi-View Stereo (MVS).
no code implementations • 15 Feb 2022 • Han Zhong, Wei Xiong, Jiyuan Tan, LiWei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
When the dataset does not have uniform coverage over all policy pairs, finding an approximate NE involves challenges in three aspects: (i) distributional shift between the behavior policy and the optimal policy, (ii) function approximation to handle large state space, and (iii) minimax optimization for equilibrium solving.
no code implementations • IEEE Transactions on Intelligent Transportation Systems 2022 • Junchen Jin, Member, IEEE, Dingding Rong, Tong Zhang, Qingyuan Ji, Haifeng Guo, Yisheng Lv, Xiaoliang Ma, and Fei-Yue Wang
This paper proposes a short-term traffic speed prediction approach, called PL-WGAN, for urban road networks, which is considered an important part of a novel parallel learning framework for traffic control and operation.
no code implementations • 11 Feb 2022 • Alekh Agarwal, Tong Zhang
We instead propose an alternative method called Minimax Regret Optimization (MRO), and show that under suitable conditions this method achieves uniformly low regret across all test distributions.
no code implementations • 11 Feb 2022 • Claudio Gentile, Zhilei Wang, Tong Zhang
We consider a batch active learning scenario where the learner adaptively issues batches of points to a labeling oracle.
1 code implementation • 21 Jan 2022 • Shizhe Diao, Zhichao Huang, Ruijia Xu, Xuechun Li, Yong Lin, Xiao Zhou, Tong Zhang
Particularly, instead of fine-tuning the model in the cloud, we adapt PLMs by prompt learning, which efficiently optimizes only a few parameters of the discrete prompts.
no code implementations • 15 Jan 2022 • Tong Zhang, Haohan Weng, Ke Yi, C. L. Philip Chen
Convolutional Neural Networks (CNNs) have exhibited their great power in a variety of vision tasks.
no code implementations • 15 Jan 2022 • Jibao Qiu, C. L. Philip Chen, Tong Zhang
In this paper, we present a simple multi-task framework for SMER, which incorporates the emotion recognition task with other emotion-related auxiliary tasks derived from the intrinsic structure of the music.
no code implementations • 14 Jan 2022 • Mengyue Zha, Kani Chen, Tong Zhang
We enhance the accuracy and generalization of univariate time series point prediction by an explainable ensemble on the fly.
1 code implementation • 14 Jan 2022 • Mengyue Zha, SiuTim Wong, Mengqi Liu, Tong Zhang, Kani Chen
This paper shows that masked autoencoder with extrapolator (ExtraMAE) is a scalable self-supervised model for time series generation.
no code implementations • CVPR 2022 • Yong Lin, Hanze Dong, Hao Wang, Tong Zhang
Generalization under distributional shift is an open challenge for machine learning.
no code implementations • 29 Dec 2021 • Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao
Inspired by the observation that low-frequency words form a more compact embedding space, we tackle this challenge from a representation learning perspective.
no code implementations • 14 Dec 2021 • Chen Liu, Zhichao Huang, Mathieu Salzmann, Tong Zhang, Sabine Süsstrunk
This lets us show that the decay in generalization performance of adversarial training is a result of the model's attempt to fit hard adversarial instances.
1 code implementation • 30 Nov 2021 • Bang Yang, Tong Zhang, Yuexian Zou
DCD is an auxiliary task that requires a caption model to learn the correspondence between video content and concepts and the co-occurrence relations between concepts.
Ranked #16 on Video Captioning on MSR-VTT
1 code implementation • 24 Nov 2021 • Ehsan Pajouheshgar, Tong Zhang, Sabine Süsstrunk
Generative Adversarial Network (GAN) based localized image editing can suffer from ambiguity between semantic attributes.
1 code implementation • NeurIPS 2021 • Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang
For the latter step, instead of using the chain rule based gradient estimators as in existing methods, we propose a variance reduced policy gradient estimator, which only requires two forward passes without backward propagation, thus achieving completely sparse training.
1 code implementation • 3 Nov 2021 • Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui
Afterward, we prove that under ideal conditions, independence-driven importance weighting algorithms could identify the variables in this set.
1 code implementation • ICLR 2022 • Rui Pan, Haishan Ye, Tong Zhang
In this paper, we propose Eigencurve, the first family of learning rate schedules that can achieve minimax optimal convergence rates (up to a constant) for SGD on quadratic objectives when the eigenvalue distribution of the underlying Hessian matrix is skewed.
no code implementations • 5 Oct 2021 • Yoav Freund, Yi-An Ma, Tong Zhang
There has been a surge of works bridging MCMC sampling and optimization, with a specific focus on translating non-asymptotic convergence guarantees for optimization problems into the analysis of Langevin algorithms in MCMC sampling.
no code implementations • 2 Oct 2021 • Tong Zhang
In this setting, we show that the standard Thompson Sampling is not aggressive enough in exploring new actions, leading to suboptimality in some pessimistic situations.
no code implementations • 29 Sep 2021 • Zhichao Huang, Chen Liu, Mathieu Salzmann, Sabine Süsstrunk, Tong Zhang
Although adversarial training and its variants currently constitute the most effective way to achieve robustness against adversarial attacks, their poor generalization limits their performance on the test samples.
1 code implementation • ICLR 2022 • Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo
However, it is limited to the case where 1) a good feature is known in advance and 2) this feature is fixed during the training: if otherwise, RLSVI suffers an unbearable computational burden to obtain the posterior samples of the parameter in the $Q$-value function.
no code implementations • 29 Sep 2021 • Yanpeng Xie, Tong Zhang, Heng Zhang, Zhendong Qu
To make the framework model-agnostic, user Multi Interests Capsule Network is designed as an auxiliary task to jointly learn item-based item representations and interest-based item representations.
1 code implementation • 26 Sep 2021 • Jiancong Chen, Yingying Zhang, Jingyi Wang, Xiaoxue Zhou, Yihua He, Tong Zhang
In this paper, we present an anchor-free ellipse detection network, namely EllipseNet, which detects the cardiac and thoracic regions in ellipse and automatically calculates the CTR and cardiac axis for fetal cardiac biometrics in 4-chamber view.
no code implementations • 20 Sep 2021 • Jieming Zhou, Tong Zhang, Pengfei Fang, Lars Petersson, Mehrtash Harandi
The core concept of GNNs is to find a representation by recursively aggregating the representations of a central node and those of its neighbors.
no code implementations • ICCV 2021 • Lewei Yao, Renjie Pi, Hang Xu, Wei zhang, Zhenguo Li, Tong Zhang
In this paper, we investigate the knowledge distillation (KD) strategy for object detection and propose an effective framework applicable to both homogeneous and heterogeneous student-teacher pairs.
no code implementations • ACL 2021 • Tong Zhang, Long Zhang, Wei Ye, Bo Li, Jinan Sun, Xiaoyu Zhu, Wen Zhao, Shikun Zhang
This paper proposes a sophisticated neural architecture to incorporate bilingual dictionaries into Neural Machine Translation (NMT) models.
1 code implementation • ACL 2021 • Shizhe Diao, Ruijia Xu, Hongjin Su, Yilei Jiang, Yan Song, Tong Zhang
In this paper, we aim to adapt a generic pretrained model with a relatively small amount of domain-specific data.
no code implementations • 20 Jul 2021 • Tong Zhang, Shuai Wang, Guoliang Li, Fan Liu, Guangxu Zhu, Rui Wang
Conventionally, the sensing and communication stages are executed sequentially, which results in excessive amount of dataset generation and uploading time.
2 code implementations • 14 Jul 2021 • Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy protection.
1 code implementation • 5 Jun 2021 • Onur Barut, Yan Luo, Tong Zhang, Weigang Li, Peilong Li
Classifying network traffic is the basis for important network applications.
no code implementations • 3 Jun 2021 • Luo Luo, Guangzeng Xie, Tong Zhang, Zhihua Zhang
This paper considers stochastic first-order algorithms for convex-concave minimax problems of the form $\min_{\bf x}\max_{\bf y}f(\bf x, \bf y)$, where $f$ can be presented by the average of $n$ individual components which are $L$-average smooth.
no code implementations • NAACL 2021 • Long Zhang, Tong Zhang, Haibo Zhang, Baosong Yang, Wei Ye, Shikun Zhang
Document-level neural machine translation (NMT) has proven to be of profound value for its effectiveness on capturing contextual information.
no code implementations • 29 May 2021 • Hanting Chen, Yunhe Wang, Chang Xu, Chao Xu, Chunjing Xu, Tong Zhang
The widely-used convolutions in deep neural networks are exactly cross-correlation to measure the similarity between input feature and convolution filters, which involves massive multiplications between float values.
no code implementations • CVPR 2021 • Lewei Yao, Renjie Pi, Hang Xu, Wei zhang, Zhenguo Li, Tong Zhang
For student morphism, weight inheritance strategy is adopted, allowing the student to flexibly update its architecture while fully utilize the predecessor's weights, which considerably accelerates the search; To facilitate dynamic distillation, an elastic teacher pool is trained via integrated progressive shrinking strategy, from which teacher detectors can be sampled without additional cost in subsequent searches.
2 code implementations • CVPR 2021 • Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
While existing NAS methods mostly design architectures on a single task, algorithms that look beyond single-task search are surging to pursue a more efficient and universal solution across various tasks.
no code implementations • 18 May 2021 • Tong Zhang, Yong liu, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao
The chit-chat-based conversational recommendation systems (CRS) provide item recommendations to users through natural language interactions.
1 code implementation • 4 May 2021 • Yan Song, Tong Zhang, Yonggang Wang, Kai-Fu Lee
Pre-trained text encoders have drawn sustaining attention in natural language processing (NLP) and shown their capability in obtaining promising results in different tasks.
1 code implementation • CVPR 2021 • Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang
Weight pruning is an effective technique to reduce the model size and inference time for deep neural networks in real-world deployments.
no code implementations • CVPR 2022 • Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang
In addition, we demonstrate that the augmentation methods are well suited for semi-supervised training and cross-dataset generalization.
no code implementations • CVPR 2021 • Jie Hong, Pengfei Fang, Weihao Li, Tong Zhang, Christian Simon, Mehrtash Harandi, Lars Petersson
Few-shot learning aims to correctly recognize query samples from unseen classes given a limited number of support samples, often by relying on global embeddings of images.
1 code implementation • 8 Apr 2021 • Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Seungryong Kim, Mathieu Salzmann, Sabine Süsstrunk
Saliency prediction has made great strides over the past two decades, with current techniques modeling low-level information, such as color, intensity and size contrasts, and high-level ones, such as attention and gaze direction for entire objects.
2 code implementations • CVPR 2021 • Aixuan Li, Jing Zhang, Yunqiu Lv, Bowen Liu, Tong Zhang, Yuchao Dai
Visual salient object detection (SOD) aims at finding the salient object(s) that attract human attention, while camouflaged object detection (COD) on the contrary intends to discover the camouflaged object(s) that hidden in the surrounding.
1 code implementation • CVPR 2021 • Zhichao Huang, Xintong Han, Jia Xu, Tong Zhang
We present a new method for few-shot human motion transfer that achieves realistic human image generation with only a small number of appearance inputs.
no code implementations • 10 Mar 2021 • Xuran Xu, Tong Zhang, Chunyan Xu, Zhen Cui, Jian Yang
We further extend graph convolution into tensor space and propose a tensor graph convolution network to extract more discriminating features from spatial-temporal graph data.
Ranked #1 on Traffic Prediction on SZ-Taxi
13 code implementations • CVPR 2021 • Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen
Convolution has been the core ingredient of modern neural networks, triggering the surge of deep learning in vision.
Ranked #707 on Image Classification on ImageNet
1 code implementation • 1 Mar 2021 • Yang Yang, Jiancong Chen, Ruixuan Wang, Ting Ma, Lingwei Wang, Jie Chen, Wei-Shi Zheng, Tong Zhang
Despite tremendous efforts, it is very challenging to generate a robust model to assist in the accurate quantification assessment of COVID-19 on chest CT images.
no code implementations • 27 Feb 2021 • Wenrui Gan, Zhulin Liu, C. L. Philip Chen, Tong Zhang
In general, the main work of this paper include: (1) propose SiLa Learning, which improves the performance of common models without increasing test parameters; (2) compares SiLa with DML and proves that SiLa can improve the generalization of the model; (3) SiLa is applied to Dynamic Neural Networks, and proved that SiLa can be used for various types of network structures.
no code implementations • 8 Feb 2021 • Haishan Ye, Tong Zhang
This leads to a decentralized PCA algorithm called \texttt{DeEPCA}, which has a convergence rate similar to that of the centralized PCA, while achieving the best communication complexity among existing decentralized PCA algorithms.
no code implementations • 26 Jan 2021 • Min Yan, Guoshan Zhang, Tong Zhang, Yueming Zhang
In inference time, we design a brand-new grouping post-processing method that relates each part instance with one single human instance and groups them together to obtain the final human-level parsing result.
no code implementations • 3 Jan 2021 • Tong Zhang, Yinfei Xu, Shuai Wang, Miaowen Wen, Rui Wang
This paper studies the problem of sum-secure degrees of freedom (SDoF) of the (M, M, N, N) multiple-input multiple-output (MIMO) interference channel with local output feedback, so as to build an information-theoretic foundation and provide practical transmission schemes for 6G-enabled vehicles-to-vehicles (V2V).
Information Theory Information Theory
no code implementations • ICCV 2021 • Yun Wang, Tong Zhang, Xueya Zhang, Zhen Cui, Yuge Huang, Pengcheng Shen, Shaoxin Li, Jian Yang
Then, a Wasserstein coupled dictionary, containing multiple pairs of counterpart graph keys with each key corresponding to one modality, is constructed for further feature learning.
2 code implementations • 1 Jan 2021 • Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
While existing NAS methods mostly design architectures on one single task, algorithms that look beyond single-task search are surging to pursue a more efficient and universal solution across various tasks.
no code implementations • 1 Jan 2021 • Xiao Zhou, Weizhong Zhang, Tong Zhang
An appealing feature of ProbMask is that the amounts of weight redundancy can be learned automatically via our constraint and thus we avoid the problem of tuning pruning rates individually for different layers in a network.
no code implementations • 1 Jan 2021 • Qing Lian, LIN Yong, Tong Zhang
We consider the domain generalization problem, where the test domain differs from the training domain.
no code implementations • 1 Jan 2021 • Wenting Zhao, Yuan Fang, Zhen Cui, Tong Zhang, Jian Yang, Wei Liu
In this paper, we propose a simple yet effective graph deformer network (GDN) to fulfill anisotropic convolution filtering on graphs, analogous to the standard convolution operation on images.
no code implementations • 30 Dec 2020 • Haishan Ye, Wei Xiong, Tong Zhang
This paper considers the decentralized composite optimization problem.
1 code implementation • 27 Dec 2020 • Cong Fang, Hanze Dong, Tong Zhang
Deep learning has received considerable empirical successes in recent years.
no code implementations • 15 Dec 2020 • Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu, Yikai Zhang, Tong Zhang, Shaoting Zhang, Dimitris N. Metaxas
As deep learning technologies advance, increasingly more data is necessary to generate general and robust models for various tasks.
no code implementations • 7 Dec 2020 • Wenqing Chen, Lulu Liu, Wentao Yang, Dong Chen, Zhengtai Liu, Yaobo Huang, Tong Zhang, Haijun Zhang, Zhonghao Liu, D. W. Shen
Utilizing angle-resolved photoemission spectroscopy and first-principles calculations, here, we demonstrate the existence of topological nodal-line states and drumheadlike surface states in centrosymmetric superconductor SnTaS2, which is a type-II superconductor with a critical transition temperature of about 3 K. The valence bands from Ta 5d orbitals and the conduction bands from Sn 5p orbitals cross each other, forming two nodal lines in the vicinity of the Fermi energy without the inclusion of spin-orbit coupling (SOC), protected by the spatial-inversion symmetry and time-reversal symmetry.
Superconductivity
3 code implementations • NeurIPS 2020 • Kai Han, Yunhe Wang, Qiulin Zhang, Wei zhang, Chunjing Xu, Tong Zhang
To this end, we summarize a tiny formula for downsizing neural architectures through a series of smaller models derived from the EfficientNet-B0 with the FLOPs constraint.
no code implementations • NeurIPS 2020 • Haishan Ye, Ziang Zhou, Luo Luo, Tong Zhang
In this paper, we propose a new method which establishes the optimal computational complexity and a near optimal communication complexity.
1 code implementation • NeurIPS 2020 • Yihong Gu, Weizhong Zhang, Cong Fang, Jason D. Lee, Tong Zhang
With the help of a new technique called {\it neural network grafting}, we demonstrate that even during the entire training process, feature distributions of differently initialized networks remain similar at each layer.