no code implementations • EMNLP 2020 • Hui Su, Xiaoyu Shen, Zhou Xiao, Zheng Zhang, Ernie Chang, Cheng Zhang, Cheng Niu, Jie zhou
In this work, we take a close look at the movie domain and present a large-scale high-quality corpus with fine-grained annotations in hope of pushing the limit of movie-domain chatbots.
no code implementations • ACL (WebNLG, INLG) 2020 • Qipeng Guo, Zhijing Jin, Ning Dai, Xipeng Qiu, xiangyang xue, David Wipf, Zheng Zhang
Text verbalization of knowledge graphs is an important problem with wide application to natural language generation (NLG) systems.
no code implementations • COLING (LaTeCHCLfL, CLFL, LaTeCH) 2020 • Alex Zhai, Zheng Zhang, Amel Fraisse, Ronald Jenn, Shelley Fisher Fishkin, Pierre Zweigenbaum
TL-Explorer is a digital humanities tool for mapping and analyzing translated literature, encompassing the World Map and the Translation Dashboard.
1 code implementation • NAACL 2022 • Zheng Zhang, Zili Zhou, Yanna Wang
Furthermore, to combine syntactic structure and semantic information, we equip the attention score matrices by syntactic mask matrices.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • ACL 2022 • Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang, Toby Li, Mo Yu, Ying Xu
Existing question answering (QA) techniques are created mainly to answer questions asked by humans.
no code implementations • ACL 2022 • Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Li, Nora Bradford, Branda Sun, Tran Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer
Through benchmarking with QG models, we show that the QG model trained on FairytaleQA is capable of asking high-quality and more diverse questions.
no code implementations • ECCV 2020 • Guo-Sen Xie, Li Liu, Fan Zhu, Fang Zhao, Zheng Zhang, Yazhou Yao, Jie Qin, Ling Shao
To exploit the progressive interactions among these regions, we represent them as a region graph, on which the parts relation reasoning is performed with graph convolutions, thus leading to our PRR branch.
1 code implementation • 30 May 2024 • Bolin Ni, Jingcheng Hu, Yixuan Wei, Houwen Peng, Zheng Zhang, Gaofeng Meng, Han Hu
In this work, we present Xwin-LM, a comprehensive suite of alignment methodologies for large language models (LLMs).
no code implementations • 27 May 2024 • Zheng Zhang, Yuntong Hu, Bo Pan, Chen Ling, Liang Zhao
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum of real-world scenarios.
no code implementations • 26 May 2024 • Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, Liang Zhao
To address this challenge, we introduce $\textbf{Graph Retrieval-Augmented Generation (GRAG)}$, which significantly enhances both the retrieval and generation processes by emphasizing the importance of subgraph structures.
no code implementations • 23 May 2024 • Zi Yang, Samridhi Choudhary, Xinfeng Xie, Cao Gao, Siegfried Kunzmann, Zheng Zhang
CoMERA achieves end-to-end rank-adaptive tensor-compressed training via a multi-objective optimization formulation, and improves the training to provide both a high compression ratio and excellent accuracy in the training process.
1 code implementation • 23 May 2024 • Xiangkun Hu, Dongyu Ru, Lin Qiu, Qipeng Guo, Tianhang Zhang, Yang Xu, Yun Luo, PengFei Liu, Yue Zhang, Zheng Zhang
In RefChecker, an extractor generates claim-triplets from a response, which are then evaluated by a checker against a reference.
1 code implementation • 29 Apr 2024 • Zechen Bai, Pichao Wang, Tianjun Xiao, Tong He, Zongbo Han, Zheng Zhang, Mike Zheng Shou
By drawing the granular classification and landscapes of hallucination causes, evaluation benchmarks, and mitigation methods, this survey aims to deepen the understanding of hallucinations in MLLMs and inspire further advancements in the field.
1 code implementation • 28 Apr 2024 • Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang
Although RDBs store vast amounts of rich, informative data spread across interconnected tables, the progress of predictive machine learning models as applied to such tasks arguably falls well behind advances in other domains such as computer vision or natural language processing.
no code implementations • 25 Apr 2024 • Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Chao Wang, Xinzhang Liu, Zihan Wang, Yu Zhao, Xin Wang, Yuyao Huang, Shuangyong Song, Yongxiang Li, Zheng Zhang, Bo Zhao, Aixin Sun, Yequan Wang, Zhongjiang He, Zhongyuan Wang, Xuelong Li, Tiejun Huang
Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications.
no code implementations • 23 Apr 2024 • Linxuan Xin, Zheng Zhang, Jinfu Wei, Ge Li, Duan Gao
Prior material creation methods had limitations in producing diverse results mainly because reconstruction-based methods relied on real-world measurements and generation-based methods were trained on relatively small material datasets.
no code implementations • 17 Apr 2024 • Xueyuan Gong, Yain-Whar Si, Zheng Zhang, Xiaochen Yuan, Ke Wang, Xinyuan Zhang, Cong Lin, Xiaoxiang Liu
MHLR supports large-scale FR training with only one GPU, which is able to accelerate the model to 1/4 of its original training time without sacrificing more than 1% accuracy.
no code implementations • 6 Apr 2024 • Duanyu Feng, Bowen Qin, Chen Huang, Zheng Zhang, Wenqiang Lei
Direct Preference Optimization (DPO), which derives reward signals directly from pairwise preference data, has shown its effectiveness on aligning Large Language Models (LLMs) with human preferences.
no code implementations • 1 Apr 2024 • Zheng Zhang, Fan Yang, Ziyan Jiang, Zheng Chen, Zhengyang Zhao, Chengyuan Ma, Liang Zhao, Yang Liu
Recent advances in large language models (LLMs) have enhanced their ability to process long input contexts.
1 code implementation • 31 Mar 2024 • Zhuotong Chen, Zihu Wang, Yifan Yang, Qianxiao Li, Zheng Zhang
This approach reduces the computational cost to that of using just the P controller, instead of the full PID control.
1 code implementation • 30 Mar 2024 • Cheng Jiayang, Lin Qiu, Chunkit Chan, Xin Liu, Yangqiu Song, Zheng Zhang
In this work, we propose an initial comprehensive framework called EventGround, which aims to tackle the problem of grounding free-texts to eventuality-centric KGs for contextualized narrative reasoning.
no code implementations • 28 Mar 2024 • Jie Wen, Zheng Zhang, Yong Xu, Bob Zhang, Lunke Fei, Guo-Sen Xie
In this paper, we propose a novel incomplete multi-view clustering network, called Cognitive Deep Incomplete Multi-view Clustering Network (CDIMC-net), to address these issues.
no code implementations • 22 Mar 2024 • Zheng Zhang, WenBo Hu, Yixing Lao, Tong He, Hengshuang Zhao
3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results while advancing real-time rendering performance.
1 code implementation • 21 Mar 2024 • Zheng Zhang, Yeyao Ma, Enming Zhang, Xiang Bai
PSALM is a powerful extension of the Large Multi-modal Model (LMM) to address the segmentation task challenges.
no code implementations • 7 Mar 2024 • Chen Li, Weiqi Wang, Jingcheng Hu, Yixuan Wei, Nanning Zheng, Han Hu, Zheng Zhang, Houwen Peng
This paper shows that the LLaMA-2 7B model with common pre-training already exhibits strong mathematical abilities, as evidenced by its impressive accuracy of 97. 7% and 72. 0% on the GSM8K and MATH benchmarks, respectively, when selecting the best response from 256 random generations.
no code implementations • 4 Mar 2024 • Amit Das, Mostafa Rahgouy, Dongji Feng, Zheng Zhang, Tathagata Bhattacharya, Nilanjana Raychawdhary, Mary Sandage, Lauramarie Pope, Gerry Dozier, Cheryl Seals
Firstly, the existing datasets primarily rely on the collection of texts containing explicit offensive keywords, making it challenging to capture implicitly offensive contents that are devoid of these keywords.
no code implementations • 19 Feb 2024 • Bo Pan, Zheng Zhang, Yifei Zhang, Yuntong Hu, Liang Zhao
To address the inherent gaps between LLMs (generative models for texts) and graph models (discriminative models for graphs), we propose first to let LLMs teach an interpreter with rich textual rationale and then let a student model mimic the interpreter's reasoning without LLMs' textual rationale.
1 code implementation • 18 Feb 2024 • Yifan Yang, Jiajun Zhou, Ngai Wong, Zheng Zhang
Various parameter-efficient fine-tuning (PEFT) techniques have been proposed to enable computationally efficient fine-tuning while maintaining model performance.
no code implementations • 21 Jan 2024 • Zheng Fang, Tianhao Chen, Dong Jiang, Zheng Zhang, Guangliang Li
Multi-agent generative adversarial imitation learning (MAGAIL) allows multi-AUV to learn from expert demonstration instead of pre-defined reward functions, but suffers from the deficiency of requiring optimal demonstrations and not surpassing provided expert demonstrations.
no code implementations • 15 Jan 2024 • Youcheng Huang, Wenqiang Lei, Zheng Zhang, Jiancheng Lv, Shuicheng Yan
In this paper, we empirically find that the effects of different contexts upon LLMs in recalling the same knowledge follow a Gaussian-like distribution.
no code implementations • 31 Dec 2023 • Yequan Zhao, Xian Xiao, Xinling Yu, Ziyue Liu, Zhixiong Chen, Geza Kurczveil, Raymond G. Beausoleil, Zheng Zhang
Despite the ultra-high speed of optical neural networks, training a PINN on an optical chip is hard due to (1) the large size of photonic devices, and (2) the lack of scalable optical memory devices to store the intermediate results of back-propagation (BP).
no code implementations • 20 Dec 2023 • Haohan Wang, Wei Feng, Yang Lu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Lixing Bo, Jingping Shao
Furthermore, for products with specific and fine-grained requirements in layout, elements, etc, a Personality-Wise Generator is devised to learn such personalized style directly from a reference image to resolve textual ambiguities, and is trained in a self-supervised manner for more efficient training data usage.
2 code implementations • 20 Dec 2023 • Weibo Gao, Qi Liu, Hao Wang, Linan Yue, Haoyang Bi, Yin Gu, Fangzhou Yao, Zheng Zhang, Xin Li, Yuanjing He
Consequently, we refine the cognitive states of cold-start students as diagnostic outcomes via virtual data, aligning with the diagnosis-oriented goal.
1 code implementation • 17 Dec 2023 • Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang, Abhinav Angirekula, Allen Zhang, Liang Zhao
Besides, existing spatial network representation learning methods can only consider networks embedded in Euclidean space, and can not well exploit the rich geometric information carried by irregular and non-uniform non-Euclidean space.
no code implementations • 14 Dec 2023 • Zhaochen Li, Fengheng Li, Wei Feng, Honghe Zhu, An Liu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao, Zhenglu Yang
At the planning stage, we propose a PlanNet to generate the layout of the product and other visual components considering both the appearance features of the product and semantic features of the text, which improves the diversity and rationality of the layouts.
1 code implementation • 14 Dec 2023 • Xingrun Xing, Li Du, Xinyuan Wang, Xianlin Zeng, Yequan Wang, Zheng Zhang, Jiajun Zhang
Specifically, we first analyze the binarization error in self-attention operations and derive the polynomials of binarization error.
2 code implementations • 1 Dec 2023 • Xiao Wang, Yaoyu Li, Tian Gan, Zheng Zhang, Jingjing Lv, Liqiang Nie
Recent advancements in video-language understanding have been established on the foundation of image-text models, resulting in promising outcomes due to the shared knowledge between images and videos.
Ranked #9 on Video Retrieval on MSR-VTT-1kA
1 code implementation • 1 Dec 2023 • Xiaoke Huang, JianFeng Wang, Yansong Tang, Zheng Zhang, Han Hu, Jiwen Lu, Lijuan Wang, Zicheng Liu
We propose a method to efficiently equip the Segment Anything Model (SAM) with the ability to generate regional captions.
1 code implementation • 22 Nov 2023 • Tianhang Zhang, Lin Qiu, Qipeng Guo, Cheng Deng, Yue Zhang, Zheng Zhang, Chenghu Zhou, Xinbing Wang, Luoyi Fu
Large Language Models (LLMs) have gained significant popularity for their impressive performance across diverse fields.
no code implementations • 22 Nov 2023 • Zheng Zhang, Cuong Nguyen, Kevin Wells, Thanh-Toan Do, Gustavo Carneiro
The ill-posedness of the LNL task requires the adoption of strong assumptions or the use of multiple noisy labels per training image, resulting in accurate models that work well in isolation but fail to optimise human-AI collaborative classification (HAI-CC).
no code implementations • 17 Nov 2023 • Ruohong Zhang, Luyu Gao, Chen Zheng, Zhen Fan, Guokun Lai, Zheng Zhang, Fangzhou Ai, Yiming Yang, Hongxia Yang
This paper introduces a novel approach to enhance LLMs by effectively extracting the relevant knowledge from domain-specific textual sources, and the adaptive training of a chatbot with domain-specific inquiries.
no code implementations • 16 Nov 2023 • Zhuotong Chen, Qianxiao Li, Zheng Zhang
Moreover, we design a surrogate retention system based on existing literature on evolutionary population dynamics to approximate the dynamics of distribution shifts on active user counts, from which the objective of achieving asymptotically fair participation is formulated as an optimal control problem, and the control variables are considered as the model parameters.
no code implementations • 1 Nov 2023 • Wenjie Ou, Dongyue Guo, Zheng Zhang, Zhishuo Zhao, Yi Lin
We present a highly accurate and simply structured CNN-based model for long-term time series forecasting tasks, called WinNet, including (i) Inter-Intra Period Encoder (I2PE) to transform 1D sequence into 2D tensor with long and short periodicity according to the predefined periodic window, (ii) Two-Dimensional Period Decomposition (TDPD) to model period-trend and oscillation terms, and (iii) Decomposition Correlation Block (DCB) to leverage the correlations of the period-trend and oscillation terms to support the prediction tasks by CNNs.
1 code implementation • 27 Oct 2023 • Houwen Peng, Kan Wu, Yixuan Wei, Guoshuai Zhao, Yuxiang Yang, Ze Liu, Yifan Xiong, Ziyue Yang, Bolin Ni, Jingcheng Hu, Ruihang Li, Miaosen Zhang, Chen Li, Jia Ning, Ruizhe Wang, Zheng Zhang, Shuguang Liu, Joe Chau, Han Hu, Peng Cheng
In this paper, we explore FP8 low-bit data formats for efficient training of large language models (LLMs).
1 code implementation • 23 Oct 2023 • Tengxiao Liu, Qipeng Guo, Yuqing Yang, Xiangkun Hu, Yue Zhang, Xipeng Qiu, Zheng Zhang
As large language models (LLMs) have shown effectiveness with different prompting methods, such as Chain of Thought, Program of Thought, we find that these methods have formed a great complementarity to each other on math reasoning tasks.
1 code implementation • IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023 • Xu Yuan, Zheng Zhang, Xunguang Wang, Lin Wu
Further, we, for the first time, formulate the formalized adversarial training of deep hashing into a unified minimax optimization under the guidance of the generated mainstay codes.
1 code implementation • 19 Oct 2023 • Cheng Jiayang, Lin Qiu, Tsz Ho Chan, Tianqing Fang, Weiqi Wang, Chunkit Chan, Dongyu Ru, Qipeng Guo, Hongming Zhang, Yangqiu Song, Yue Zhang, Zheng Zhang
Analogy-making between narratives is crucial for human reasoning.
1 code implementation • 11 Oct 2023 • Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Wenyang Gao, Xuming Hu, Zehan Qi, Yidong Wang, Linyi Yang, Jindong Wang, Xing Xie, Zheng Zhang, Yue Zhang
This survey addresses the crucial issue of factuality in Large Language Models (LLMs).
no code implementations • 7 Oct 2023 • Zheng Zhang, Hossein Amiri, Zhenke Liu, Andreas Züfle, Liang Zhao
Identifying anomalous human spatial trajectory patterns can indicate dynamic changes in mobility behavior with applications in domains like infectious disease monitoring and elderly care.
no code implementations • 7 Oct 2023 • Yuntong Hu, Zheng Zhang, Liang Zhao
Large language models (LLMs) have achieved impressive performance on many natural language processing tasks.
no code implementations • 7 Oct 2023 • Zheng Zhang, Liang Zhao
Deep learning has shown remarkable success in the field of clustering recently.
no code implementations • 7 Oct 2023 • Zheng Zhang, Chen Zheng, Da Tang, Ke Sun, Yukun Ma, Yingtong Bu, Xun Zhou, Liang Zhao
This paper introduces a multifaceted methodology for fine-tuning and evaluating large language models (LLMs) for specialized monetization tasks.
1 code implementation • 3 Oct 2023 • Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
Our extensive experiments show that DeepZero achieves state-of-the-art (SOTA) accuracy on ResNet-20 trained on CIFAR-10, approaching FO training performance for the first time.
1 code implementation • 28 Sep 2023 • Yiming Ju, Zheng Zhang
KLoB can serve as a benchmark for evaluating existing locating methods in language models, and can contributes a method to reassessing the validity of locality hypothesis of factual knowledge.
1 code implementation • ICCV 2023 • Ke Fan, Jingshi Lei, Xuelin Qian, Miaopeng Yu, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu
Furthermore, we propose a multi-view fusion layer based temporal module which is equipped with a set of object slots and interacts with features from different views by attention mechanism to fulfill sufficient object representation completion.
1 code implementation • 20 Sep 2023 • Yazhou Zhu, Shidong Wang, Tong Xin, Zheng Zhang, Haofeng Zhang
In this work, we present an approach to extract multiple representative sub-regions from a given support medical image, enabling fine-grained selection over the generated image regions.
no code implementations • ICCV 2023 • Ke Fan, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao, Carl-Johann Simon-Gabriel, Mike Zheng Shou, Francesco Locatello, Bernt Schiele, Thomas Brox, Zheng Zhang, Yanwei Fu, Tong He
In this paper, we show that recent advances in video representation learning and pre-trained vision-language models allow for substantial improvements in self-supervised video object localization.
1 code implementation • 7 Sep 2023 • Zigang Geng, Binxin Yang, Tiankai Hang, Chen Li, Shuyang Gu, Ting Zhang, Jianmin Bao, Zheng Zhang, Han Hu, Dong Chen, Baining Guo
We present InstructDiffusion, a unifying and generic framework for aligning computer vision tasks with human instructions.
no code implementations • 7 Sep 2023 • Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Xuying Meng, Siqi Fan, Peng Han, Jing Li, Li Du, Bowen Qin, Zheng Zhang, Aixin Sun, Yequan Wang
We demonstrate that a 101B-parameter LLM with 0. 31T tokens can be trained with a budget of 100K US dollars.
1 code implementation • ICCV 2023 • Zixu Zhao, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik Zietlow, Carl-Johann Simon-Gabriel, Bing Shuai, Zhuowen Tu, Thomas Brox, Bernt Schiele, Yanwei Fu, Francesco Locatello, Zheng Zhang, Tianjun Xiao
Unsupervised object-centric learning methods allow the partitioning of scenes into entities without additional localization information and are excellent candidates for reducing the annotation burden of multiple-object tracking (MOT) pipelines.
1 code implementation • ICCV 2023 • Jianxiong Gao, Xuelin Qian, Yikai Wang, Tianjun Xiao, Tong He, Zheng Zhang, Yanwei Fu
To address this issue, we propose a convolution refine module to inject fine-grained information and provide a more precise amodal object segmentation based on visual features and coarse-predicted segmentation.
1 code implementation • 28 Aug 2023 • Fengling Li, Lei Zhu, Tianshi Wang, Jingjing Li, Zheng Zhang, Heng Tao Shen
With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval methods struggle to meet the needs of users demanding access to data from various modalities.
no code implementations • 18 Aug 2023 • Yequan Zhao, Xinling Yu, Zhixiong Chen, Ziyue Liu, Sijia Liu, Zheng Zhang
Backward propagation (BP) is widely used to compute the gradients in neural network training.
1 code implementation • 3 Aug 2023 • Yutong Lin, Yuhui Yuan, Zheng Zhang, Chen Li, Nanning Zheng, Han Hu
This paper presents an improved DETR detector that maintains a "plain" nature: using a single-scale feature map and global cross-attention calculations without specific locality constraints, in contrast to previous leading DETR-based detectors that reintroduce architectural inductive biases of multi-scale and locality into the decoder.
no code implementations • ICCV 2023 • Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Zi Huang, Mahsa Baktashmotlagh
Achieving a reliable LiDAR-based object detector in autonomous driving is paramount, but its success hinges on obtaining large amounts of precise 3D annotations.
1 code implementation • 10 Jul 2023 • Zheng Zhang, XiaoLei Zhang, Yaolei Qi, Guanyu Yang
To this end, we propose partial vessels annotation (PVA) based on the challenges of coronary artery segmentation and clinical diagnostic characteristics.
no code implementations • 7 Jul 2023 • Xuesong Wang, Dongsheng Zhang, Zheng Zhang
With the development of CNC machine tools toward high speed and high precision, the traditional static design methods can hardly meet the demand.
1 code implementation • 26 Jun 2023 • Yun Guo, Wei Feng, Zheng Zhang, Xiancong Ren, Yaoyu Li, Jingjing Lv, Xin Zhu, Zhangang Lin, Jingping Shao
Product image segmentation is vital in e-commerce.
no code implementations • 19 Jun 2023 • Dongyu Ru, Lin Qiu, Xipeng Qiu, Yue Zhang, Zheng Zhang
Discourse analysis is an important task because it models intrinsic semantic structures between sentences in a document.
1 code implementation • 18 Jun 2023 • Yan Zhuang, Qi Liu, Yuting Ning, Weizhe Huang, Rui Lv, Zhenya Huang, Guanhao Zhao, Zheng Zhang, Qingyang Mao, Shijin Wang, Enhong Chen
Different tests for different models using efficient adaptive testing -- we believe this has the potential to become a new norm in evaluating large language models.
1 code implementation • 15 Jun 2023 • Fengheng Li, An Liu, Wei Feng, Honghe Zhu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao
To advance research in this field, we have constructed a poster layout dataset named CGL-Dataset V2.
no code implementations • 8 Jun 2023 • Yifan Yang, Alec Koppel, Zheng Zhang
In this paper, we propose a novel gradient-based approach to enable the detection of noisy labels for the online learning of model parameters, named Online Gradient-based Robust Selection (OGRS).
1 code implementation • 6 Jun 2023 • Chujie Zheng, Pei Ke, Zheng Zhang, Minlie Huang
It has always been an important yet challenging problem to control language models to avoid generating texts with undesirable attributes, such as toxic language and unnatural repetition.
no code implementations • 1 Jun 2023 • Zi Yang, Samridhi Choudhary, Siegfried Kunzmann, Zheng Zhang
To improve the convergence, a layer-by-layer distillation is applied to distill a quantized and tensor-compressed student model from a pre-trained transformer.
1 code implementation • 30 May 2023 • Yuqing Yang, Qipeng Guo, Xiangkun Hu, Yue Zhang, Xipeng Qiu, Zheng Zhang
Motivated by the fact that all event structures can be inferred from AMR, this work reformulates EAE as a link prediction problem on AMR graphs.
1 code implementation • 26 May 2023 • Cunxiang Wang, Zhikun Xu, Qipeng Guo, Xiangkun Hu, Xuefeng Bai, Zheng Zhang, Yue Zhang
The Open-Domain Question Answering (ODQA) task involves retrieving and subsequently generating answers from fine-grained relevant passages within a database.
1 code implementation • NeurIPS 2023 • Cunxiang Wang, Sirui Cheng, Qipeng Guo, Yuanhao Yue, Bowen Ding, Zhikun Xu, Yidong Wang, Xiangkun Hu, Zheng Zhang, Yue Zhang
This study focuses on the evaluation of the Open Question Answering (Open-QA) task, which can directly estimate the factuality of large language models (LLMs).
1 code implementation • 12 May 2023 • Yuan Tian, Zheng Zhang, Zheng Ning, Toby Jia-Jun Li, Jonathan K. Kummerfeld, Tianyi Zhang
Many techniques have been proposed to automatically generate SQL from natural language, but they suffer from two issues: (1) they still make many mistakes, particularly for complex queries, and (2) they do not provide a flexible way for non-expert users to validate and refine incorrect queries.
1 code implementation • 4 May 2023 • Yiqun Yao, Zheng Zhang, Jing Li, Yequan Wang
In terms of growth schedule, the impact of each single dimension on a schedule's efficiency is under-explored by existing work.
1 code implementation • 2 May 2023 • Dongyue Guo, Zheng Zhang, Zhen Yan, Jianwei Zhang, Yi Lin
Additionally, the Gray code representation and the differential prediction paradigm are designed to cope with the high-bit misclassifications of the BE representation, which significantly reduces the outliers in the predictions.
no code implementations • 25 Apr 2023 • Lei Shi, Tianyu Gao, Zheng Zhang, Junxing Zhang
Deep learning based models for medical image segmentation have made great progress in recent years.
no code implementations • 16 Apr 2023 • Zheng Zhang, Jie Gao, Ranjodh Singh Dhaliwal, Toby Jia-Jun Li
In argumentative writing, writers must brainstorm hierarchical writing goals, ensure the persuasiveness of their arguments, and revise and organize their plans through drafting.
1 code implementation • 30 Mar 2023 • Jie Xu, Yazhou Ren, Xiaolong Wang, Lei Feng, Zheng Zhang, Gang Niu, Xiaofeng Zhu
Multi-view clustering (MVC) aims at exploring category structures among multi-view data in self-supervised manners.
1 code implementation • 15 Mar 2023 • Sucheng Ren, Fangyun Wei, Samuel Albanie, Zheng Zhang, Han Hu
Deep supervision, which involves extra supervisions to the intermediate features of a neural network, was widely used in image classification in the early deep learning era since it significantly reduces the training difficulty and eases the optimization like avoiding gradient vanish over the vanilla training.
no code implementations • 28 Feb 2023 • Yifan Yang, Chang Liu, Zheng Zhang
Online optimization has gained increasing interest due to its capability of tracking real-world streaming data.
no code implementations • 25 Feb 2023 • Ziyue Liu, Yixing Li, Jing Hu, Xinling Yu, Shinyu Shiau, Xin Ai, Zhiyu Zeng, Zheng Zhang
In this paper, for the first time, we propose DeepOHeat, a physics-aware operator learning framework to predict the temperature field of a family of heat equations with multiple parametric or non-parametric design configurations.
3 code implementations • CVPR 2023 • Mengde Xu, Zheng Zhang, Fangyun Wei, Han Hu, Xiang Bai
A side network is attached to a frozen CLIP model with two branches: one for predicting mask proposals, and the other for predicting attention bias which is applied in the CLIP model to recognize the class of masks.
no code implementations • 23 Feb 2023 • Xinling Yu, José E. C. Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang
PIFON-EPT is the first method that can simultaneously reconstruct EP and transmit fields from incomplete noisy MR measurements, providing new opportunities for EPT research.
no code implementations • 17 Feb 2023 • Yequan Zhao, Xian Xiao, Geza Kurczveil, Raymond G. Beausoleil, Zheng Zhang
We propose the first tensorized optical multimodal fusion network architecture with a self-attention mechanism and low-rank tensor fusion.
no code implementations • 22 Jan 2023 • Junyong You, Zheng Zhang
A sequential spatial-channel attention module is proposed to simulate the visual attention and contrast sensitivity mechanisms that are crucial for content recognition and quality assessment.
no code implementations • 18 Jan 2023 • Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang
A key performance bottleneck when training graph neural network (GNN) models on large, real-world graphs is loading node features onto a GPU.
1 code implementation • ICCV 2023 • Jia Ning, Chen Li, Zheng Zhang, Zigang Geng, Qi Dai, Kun He, Han Hu
With these new techniques and other designs, we show that the proposed general-purpose task-solver can perform both instance segmentation and depth estimation well.
Ranked #14 on Monocular Depth Estimation on NYU-Depth V2
2 code implementations • CVPR 2023 • Sucheng Ren, Fangyun Wei, Zheng Zhang, Han Hu
Our TinyMIM model of tiny size achieves 79. 6% top-1 accuracy on ImageNet-1K image classification, which sets a new record for small vision models of the same size and computation budget.
no code implementations • CVPR 2023 • Yixuan Wei, Yue Cao, Zheng Zhang, Houwen Peng, Zhuliang Yao, Zhenda Xie, Han Hu, Baining Guo
This paper presents a method that effectively combines two prevalent visual recognition methods, i. e., image classification and contrastive language-image pre-training, dubbed iCLIP.
1 code implementation • ICCV 2023 • Jianfeng Dong, Minsong Zhang, Zheng Zhang, Xianke Chen, Daizong Liu, Xiaoye Qu, Xun Wang, Baolong Liu
During the knowledge distillation, an inheritance student branch is devised to absorb the knowledge from the teacher model.
1 code implementation • ICCV 2023 • Yixuan Wei, Han Hu, Zhenda Xie, Ze Liu, Zheng Zhang, Yue Cao, Jianmin Bao, Dong Chen, Baining Guo
Experiments suggest that the feature map distillation approach significantly boosts the fine-tuning performance of CLIP models on several typical downstream vision tasks.
1 code implementation • ICCV 2023 • Yutong Lin, Yuhui Yuan, Zheng Zhang, Chen Li, Nanning Zheng, Han Hu
This paper presents an improved DETR detector that maintains a "plain" nature: using a single-scale feature map and global cross-attention calculations without specific locality constraints, in contrast to previous leading DETR-based detectors that reintroduce architectural inductive biases of multi-scale and locality into the decoder.
no code implementations • 25 Dec 2022 • Jiarui Jin, Yangkun Wang, Weinan Zhang, Quan Gan, Xiang Song, Yong Yu, Zheng Zhang, David Wipf
However, existing methods lack elaborate design regarding the distinctions between two tasks that have been frequently overlooked: (i) edges only constitute the topology in the node classification task but can be used as both the topology and the supervisions (i. e., labels) in the edge prediction task; (ii) the node classification makes prediction over each individual node, while the edge prediction is determinated by each pair of nodes.
1 code implementation • 7 Dec 2022 • Zheng Zhang, Qingrui Zhang, Bo Zhu, Xiaohan Wang, Tianjiang Hu
In this paper, a novel algorithm named EASpace (Enhanced Action Space) is proposed, which formulates macro actions in an alternative form to accelerate the learning process using multiple available sub-optimal expert policies.
1 code implementation • 5 Dec 2022 • Xi Zhao, Wei Feng, Zheng Zhang, Jingjing Lv, Xin Zhu, Zhangang Lin, Jinghe Hu, Jingping Shao
Recently, segmentation-based methods are quite popular in scene text detection, which mainly contain two steps: text kernel segmentation and expansion.
no code implementations • 4 Dec 2022 • Qi Zhu, Fei Mi, Zheng Zhang, Yasheng Wang, Yitong Li, Xin Jiang, Qun Liu, Xiaoyan Zhu, Minlie Huang
For the former, the grounding knowledge consists of keywords extracted from the response.
1 code implementation • 30 Nov 2022 • Qi Zhu, Christian Geishauser, Hsien-Chin Lin, Carel van Niekerk, Baolin Peng, Zheng Zhang, Michael Heck, Nurul Lubis, Dazhen Wan, Xiaochen Zhu, Jianfeng Gao, Milica Gašić, Minlie Huang
Task-oriented dialogue (TOD) systems function as digital assistants, guiding users through various tasks such as booking flights or finding restaurants.
1 code implementation • 21 Nov 2022 • Zixin Zhu, Yixuan Wei, JianFeng Wang, Zhe Gan, Zheng Zhang, Le Wang, Gang Hua, Lijuan Wang, Zicheng Liu, Han Hu
The image captioning task is typically realized by an auto-regressive method that decodes the text tokens one by one.
no code implementations • 3 Nov 2022 • Yutong Lin, Ze Liu, Zheng Zhang, Han Hu, Nanning Zheng, Stephen Lin, Yue Cao
In this paper, we present a study of frozen pretrained models when applied to diverse and representative computer vision tasks, including object detection, semantic segmentation and video action recognition.
Ranked #3 on Action Recognition In Videos on Kinetics-400
1 code implementation • 31 Oct 2022 • Tengxiao Liu, Qipeng Guo, Xiangkun Hu, Yue Zhang, Xipeng Qiu, Zheng Zhang
RLET iteratively performs single step reasoning with sentence selection and deduction generation modules, from which the training signal is accumulated across the tree with elaborately designed aligned reward function that is consistent with the evaluation.
1 code implementation • 28 Oct 2022 • Qipeng Guo, Yuqing Yang, Hang Yan, Xipeng Qiu, Zheng Zhang
In this paper, we investigate the root cause of the underwhelming performance of the existing generative DocRE models and discover that the culprit is the inadequacy of the training paradigm, instead of the capacities of the models.
no code implementations • 27 Oct 2022 • Chengyu Huang, Zheng Zhang, Hao Fei, Lizi Liao
Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations.
no code implementations • 23 Oct 2022 • Xinling Yu, José E. C. Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang
Electrical properties (EP), namely permittivity and electric conductivity, dictate the interactions between electromagnetic waves and biological tissue.
1 code implementation • 23 Oct 2022 • Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang
The key intuition is that the occluded part of an object can be explained away if that part is visible in other frames, possibly deformed as long as the deformation can be reasonably learned.
4 code implementations • 3 Oct 2022 • Weicong Liang, Yuhui Yuan, Henghui Ding, Xiao Luo, WeiHong Lin, Ding Jia, Zheng Zhang, Chao Zhang, Han Hu
Vision transformers have recently achieved competitive results across various vision tasks but still suffer from heavy computation costs when processing a large number of tokens.
3 code implementations • 29 Sep 2022 • Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
Humans naturally decompose their environment into entities at the appropriate level of abstraction to act in the world.
1 code implementation • 20 Sep 2022 • Changtong Zan, Keqin Peng, Liang Ding, Baopu Qiu, Boan Liu, Shwai He, Qingyu Lu, Zheng Zhang, Chuang Liu, Weifeng Liu, Yibing Zhan, DaCheng Tao
As for model sizes, we scale the Transformer-Big up to the extremely large model that owns nearly 4. 7 Billion parameters, to fully enhance the model capacity for our Vega-MT.
Ranked #1 on Machine Translation on WMT 2022 English-Russian
1 code implementation • 16 Sep 2022 • Jia Zhang, Yukun Huang, Zheng Zhang, Yuhang Shi
There has been growing research interest in using deep learning based method to achieve fully automated segmentation of lesion in Positron emission tomography computed tomography(PET CT) scans for the prognosis of various cancers.
no code implementations • 31 Aug 2022 • Kun Liu, Huiyuan Fu, Zheng Zhang, Huanpu Yin
This paper provides a brief overview of our submission to the no interaction track of SAPIEN ManiSkill Challenge 2021.
1 code implementation • 23 Aug 2022 • Lingfeng li, Huaiwei Cong, Gangming Zhao, Junran Peng, Zheng Zhang, Jinpeng Li
However, due to the tissue overlap, X-ray images are difficult to provide fine-grained features for early diagnosis.
1 code implementation • 23 Aug 2022 • Xin Wei, Huaiwei Cong, Zheng Zhang, Junran Peng, Guoping Chen, Jinpeng Li
Long-term vertebral fractures severely affect the life quality of patients, causing kyphotic, lumbar deformity and even paralysis.
1 code implementation • 18 Aug 2022 • Jinfeng Zhou, Chujie Zheng, Bo wang, Zheng Zhang, Minlie Huang
Empathetic conversation is psychologically supposed to be the result of conscious alignment and interaction between the cognition and affection of empathy.
1 code implementation • 17 Aug 2022 • Jie Wen, Zheng Zhang, Lunke Fei, Bob Zhang, Yong Xu, Zhao Zhang, Jinxing Li
However, in practical applications, such as disease diagnosis, multimedia analysis, and recommendation system, it is common to observe that not all views of samples are available in many cases, which leads to the failure of the conventional multi-view clustering methods.
1 code implementation • 2 Aug 2022 • Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martin Santillan Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang, Lucy Yip, Liat Ein-Dor, Lena Dankin, Ilya Shnayderman, Ranit Aharonov, Yunyao Li, Naftali Liberman, Philip Levin Slesarev, Gwilym Newton, Shila Ofek-Koifman, Noam Slonim, Yoav Katz
Text classification can be useful in many real-world scenarios, saving a lot of time for end users.
no code implementations • 11 Jul 2022 • Jie Qin, Shuaihang Yuan, Jiaxin Chen, Boulbaba Ben Amor, Yi Fang, Nhat Hoang-Xuan, Chi-Bien Chu, Khoi-Nguyen Nguyen-Ngoc, Thien-Tri Cao, Nhat-Khang Ngo, Tuan-Luc Huynh, Hai-Dang Nguyen, Minh-Triet Tran, Haoyang Luo, Jianning Wang, Zheng Zhang, Zihao Xin, Yang Wang, Feng Wang, Ying Tang, Haiqin Chen, Yan Wang, Qunying Zhou, Ji Zhang, Hongyuan Wang
We define two SBSR tasks and construct two benchmarks consisting of more than 46, 000 CAD models, 1, 700 realistic models, and 145, 000 sketches in total.
no code implementations • 9 Jul 2022 • Lin Wu, Lingqiao Liu, Yang Wang, Zheng Zhang, Farid Boussaid, Mohammed Bennamoun
It is a challenging and practical problem since the query images often suffer from resolution degradation due to the different capturing conditions from real-world cameras.
no code implementations • 4 Jul 2022 • Canran Li, Dongnan Liu, Haoran Li, Zheng Zhang, Guangming Lu, Xiaojun Chang, Weidong Cai
In this work, we propose a novel deep neural network, namely Category-Aware feature alignment and Pseudo-Labelling Network (CAPL-Net) for UDA nuclei instance segmentation and classification.
no code implementations • 4 Jul 2022 • Ziyue Liu, Xinling Yu, Zheng Zhang
Physics-informed neural networks (PINNs) have been increasingly employed due to their capability of modeling complex physics systems.
1 code implementation • 26 Jun 2022 • Zhuotong Chen, Qianxiao Li, Zheng Zhang
While numerous attack and defense techniques have been developed, this work investigates the robustness issue from a new angle: can we design a self-healing neural network that can automatically detect and fix the vulnerability issue by itself?
1 code implementation • 14 Jun 2022 • Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David Wipf
Prediction over tabular data is an essential and fundamental problem in many important downstream tasks.
1 code implementation • CVPR 2023 • Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Yixuan Wei, Qi Dai, Han Hu
Our study reveals that: (i) Masked image modeling is also demanding on larger data.
no code implementations • 6 Jun 2022 • Mengqi Yao, Meghana Bharadwaj, Zheng Zhang, Baihong Jin, Duncan S. Callaway
Our data include historical ignition and wire-down points triggered by grid infrastructure collected between 2015 to 2019 in Pacific Gas & Electricity territory along with various weather, vegetation, and very high resolution data on grid infrastructure including location, age, materials.
1 code implementation • 27 May 2022 • Yixuan Wei, Han Hu, Zhenda Xie, Zheng Zhang, Yue Cao, Jianmin Bao, Dong Chen, Baining Guo
These properties, which we aggregately refer to as optimization friendliness, are identified and analyzed by a set of attention- and optimization-related diagnosis tools.
Ranked #2 on Instance Segmentation on COCO test-dev (using extra training data)
1 code implementation • CVPR 2023 • Zhenda Xie, Zigang Geng, Jingcheng Hu, Zheng Zhang, Han Hu, Yue Cao
In this paper, we compare MIM with the long-dominant supervised pre-trained models from two perspectives, the visualizations and the experiments, to uncover their key representational differences.
Ranked #3 on Depth Estimation on NYU-Depth V2
no code implementations • 21 May 2022 • Ryan Solgi, Zichang He, William Jiahua Liang, Zheng Zhang
Various tensor decomposition methods have been proposed for data compression.
no code implementations • 24 Apr 2022 • Zheng Zhang, Yingsheng Ji, Jiachen Shen, Xi Zhang, Guangwen Yang
Risk assessment is a substantial problem for financial institutions that has been extensively studied both for its methodological richness and its various practical applications.
1 code implementation • 23 Apr 2022 • Xiangkun Hu, Junqi Dai, Hang Yan, Yi Zhang, Qipeng Guo, Xipeng Qiu, Zheng Zhang
We propose Dialogue Meaning Representation (DMR), a pliable and easily extendable representation for task-oriented dialogue.
no code implementations • 22 Apr 2022 • Yixuan Wei, Yue Cao, Zheng Zhang, Zhuliang Yao, Zhenda Xie, Han Hu, Baining Guo
Second, we convert the image classification problem from learning parametric category classifier weights to learning a text encoder as a meta network to generate category classifier weights.
no code implementations • 16 Apr 2022 • Zheng Zhang, Liang Ding, Dazhao Cheng, Xuebo Liu, Min Zhang, DaCheng Tao
Data augmentations (DA) are the cores to achieving robust sequence-to-sequence learning on various natural language processing (NLP) tasks.
no code implementations • 28 Mar 2022 • Junyong You, Zheng Zhang
Meanwhile, representative features for image quality perception in the spatial and frequency domains can also be derived from the IQA model, which are then fed into another windowed transformer architecture for video quality assessment (VQA).
1 code implementation • 26 Mar 2022 • Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Nora Bradford, Branda Sun, Tran Bao Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer
Through benchmarking with QG models, we show that the QG model trained on FairytaleQA is capable of asking high-quality and more diverse questions.
Ranked #1 on Question Generation on FairytaleQA
1 code implementation • 17 Mar 2022 • Yuxian Gu, Jiaxin Wen, Hao Sun, Yi Song, Pei Ke, Chujie Zheng, Zheng Zhang, Jianzhu Yao, Lei Liu, Xiaoyan Zhu, Minlie Huang
Large-scale pre-training has shown remarkable performance in building open-domain dialogue systems.
no code implementations • 9 Mar 2022 • Zheng Zhang, Xiaohan Wang, Qingrui Zhang, Tianjiang Hu
It is shown by numerical simulations that the proposed hybrid design outperforms the pursuit policies either learned from vanilla reinforcement learning or designed by the potential field method.
1 code implementation • 26 Feb 2022 • Chujie Zheng, Sahand Sabour, Jiaxin Wen, Zheng Zhang, Minlie Huang
Applying this approach, we construct AugESC, an augmented dataset for the ESC task, which largely extends the scale and topic coverage of the crowdsourced ESConv corpus.
1 code implementation • 13 Feb 2022 • Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li
Despite its benefits for children's skill development and parent-child bonding, many parents do not often engage in interactive storytelling by having story-related dialogues with their child due to limited availability or challenges in coming up with appropriate questions.
no code implementations • 24 Jan 2022 • Xiangkun Hu, Hang Yan, Qipeng Guo, Xipeng Qiu, Weinan Zhang, Zheng Zhang
Knowledge and expertise in the real-world can be disjointedly owned.
1 code implementation • 18 Jan 2022 • Cole Hawkins, Alec Koppel, Zheng Zhang
A fundamental challenge in Bayesian inference is efficient representation of a target distribution.
no code implementations • 31 Dec 2021 • Zheng Zhang, Liangliang Xu, Levent Yilmaz, Bo Liu
Despite recent advances in modern machine learning algorithms, the opaqueness of their underlying mechanisms continues to be an obstacle in adoption.
BIG-bench Machine Learning Explainable artificial intelligence +2
2 code implementations • 29 Dec 2021 • Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Han Hu, Xiang Bai
However, semantic segmentation and the CLIP model perform on different visual granularity, that semantic segmentation processes on pixels while CLIP performs on images.
no code implementations • NeurIPS 2021 • Longyuan Li, Jian Yao, Li Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang
Learning the distribution of future trajectories conditioned on the past is a crucial problem for understanding multi-agent systems.
1 code implementation • NeurIPS 2021 • Zheng Zhang, Liang Zhao
Specifically, a provably information-lossless and roto-translation invariant representation of spatial information on networks is presented.
19 code implementations • CVPR 2022 • Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, Baining Guo
Three main techniques are proposed: 1) a residual-post-norm method combined with cosine attention to improve training stability; 2) A log-spaced continuous position bias method to effectively transfer models pre-trained using low-resolution images to downstream tasks with high-resolution inputs; 3) A self-supervised pre-training method, SimMIM, to reduce the needs of vast labeled images.
Ranked #4 on Image Classification on ImageNet V2 (using extra training data)
4 code implementations • CVPR 2022 • Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai, Han Hu
We also leverage this approach to facilitate the training of a 3B model (SwinV2-G), that by $40\times$ less data than that in previous practice, we achieve the state-of-the-art on four representative vision benchmarks.
Representation Learning Self-Supervised Image Classification +1
1 code implementation • NeurIPS 2021 • Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Stephen Lin, Han Hu, Xiang Bai
We introduce MixTraining, a new training paradigm for object detection that can improve the performance of existing detectors for free.
no code implementations • ICLR 2022 • Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
In this regard, it has recently been proposed to use a randomly-selected portion of the training labels as GNN inputs, concatenated with the original node features for making predictions on the remaining labels.
no code implementations • ICLR 2022 • Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan
Prevailing methods for relation prediction in heterogeneous graphs aim at learning latent representations (i. e., embeddings) of observed nodes and relations, and thus are limited to the transductive setting where the relation types must be known during training.
no code implementations • 29 Sep 2021 • Minjie Wang, Haoming Lu, Yu Gai, Lesheng Jin, Zihao Ye, Zheng Zhang
Despite substantial efforts from the deep learning system community to relieve researchers and practitioners from the burden of implementing models with ever-growing complexity, a considerable lingual gap remains between developing models in the language of mathematics and implementing them in the languages of computer.
2 code implementations • 8 Sep 2021 • Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Mo Yu, Ying Xu
Existing question answering (QA) techniques are created mainly to answer questions asked by humans.
no code implementations • 7 Sep 2021 • Guan-Nan Dong, Chi-Man Pun, Zheng Zhang
To this end, we propose a novel deep collaborative multi-modal learning (DCML) to integrate the underlying information presented in facial properties in an adaptive manner to strengthen the facial details for effective unsupervised kinship verification.
no code implementations • 7 Sep 2021 • Guan-Nan Dong, Chi-Man Pun, Zheng Zhang
Specifically, we take parents and children as a whole to extract the expressive local and non-local features.
2 code implementations • 3 Aug 2021 • Hao Zhou, Pei Ke, Zheng Zhang, Yuxian Gu, Yinhe Zheng, Chujie Zheng, Yida Wang, Chen Henry Wu, Hao Sun, Xiaocong Yang, Bosi Wen, Xiaoyan Zhu, Minlie Huang, Jie Tang
Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue data and the model size compared with English ones.
1 code implementation • 12 Jul 2021 • Bingzhi Chen, Yishu Liu, Zheng Zhang, Guangming Lu, Adams Wai Kin Kong
Accurate segmentation of organs or lesions from medical images is crucial for reliable diagnosis of diseases and organ morphometry.
1 code implementation • SIGIR 2021 • Lizi Liao, Le Hong Long, Zheng Zhang, Minlie Huang, Tat-Seng Chua
Second, a set of benchmark results for dialogue state tracking, conversational recommendation, response generation as well as a unified model for multiple tasks are reported.
Ranked #2 on Dialogue State Tracking on MMConv
2 code implementations • ICCV 2021 • Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto
Our hierarchical GNN uses a novel approach to merge connected components predicted at each level of the hierarchy to form a new graph at the next level.
no code implementations • 30 Jun 2021 • Yang Li, Yadan Luo, Zheng Zhang, Shazia W. Sadiq, Peng Cui
It aims at suggesting the next POI to a user in spatial and temporal context, which is a practical yet challenging task in various applications.
14 code implementations • CVPR 2022 • Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, Han Hu
The vision community is witnessing a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major video recognition benchmarks.
Ranked #28 on Action Classification on Kinetics-600 (using extra training data)
8 code implementations • ICCV 2021 • Mengde Xu, Zheng Zhang, Han Hu, JianFeng Wang, Lijuan Wang, Fangyun Wei, Xiang Bai, Zicheng Liu
This paper presents an end-to-end semi-supervised object detection approach, in contrast to previous more complex multi-stage methods.
Ranked #6 on Semi-Supervised Object Detection on COCO 100% labeled data (using extra training data)
1 code implementation • 12 Jun 2021 • Ailiang Lin, Bingzhi Chen, Jiayu Xu, Zheng Zhang, Guangming Lu
To alleviate these problems, we propose a novel deep medical image segmentation framework called Dual Swin Transformer U-Net (DS-TransUNet), which might be the first attempt to concurrently incorporate the advantages of hierarchical Swin Transformer into both encoder and decoder of the standard U-shaped architecture to enhance the semantic segmentation quality of varying medical images.
3 code implementations • ACL 2021 • Hang Yan, Junqi Dai, Tuo ji, Xipeng Qiu, Zheng Zhang
Aspect-based Sentiment Analysis (ABSA) aims to identify the aspect terms, their corresponding sentiment polarities, and the opinion terms.
Ranked #1 on Aspect Sentiment Triplet Extraction on SemEval
Aspect-Based Sentiment Analysis Aspect-oriented Opinion Extraction +2
1 code implementation • ACL 2021 • Hang Yan, Tao Gui, Junqi Dai, Qipeng Guo, Zheng Zhang, Xipeng Qiu
To that end, we propose to formulate the NER subtasks as an entity span sequence generation task, which can be solved by a unified sequence-to-sequence (Seq2Seq) framework.
Ranked #10 on Nested Named Entity Recognition on GENIA
1 code implementation • CVPR 2021 • Xunguang Wang, Zheng Zhang, Baoyuan Wu, Fumin Shen, Guangming Lu
However, deep hashing networks are vulnerable to adversarial examples, which is a practical secure problem but seldom studied in hashing-based retrieval field.
1 code implementation • 12 May 2021 • Yansong Tang, Zhenyu Jiang, Zhenda Xie, Yue Cao, Zheng Zhang, Philip H. S. Torr, Han Hu
Previous cycle-consistency correspondence learning methods usually leverage image patches for training.
no code implementations • 11 May 2021 • Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao
This paper emphasizes the importance and efficacy of training, quantization and accelerator design, and calls for more research breakthroughs in the area for AI on the edge.
6 code implementations • 10 May 2021 • Zhenda Xie, Yutong Lin, Zhuliang Yao, Zheng Zhang, Qi Dai, Yue Cao, Han Hu
We are witnessing a modeling shift from CNN to Transformers in computer vision.
Ranked #75 on Self-Supervised Image Classification on ImageNet
1 code implementation • Findings (EMNLP) 2021 • Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein
However, the next word prediction training objective is still misaligned with the target zero-shot learning objective.
4 code implementations • ICCV 2021 • Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong
Instead of grouping local points to each object candidate, our method computes the feature of an object from all the points in the point cloud with the help of an attention mechanism in the Transformers \cite{vaswani2017attention}, where the contribution of each point is automatically learned in the network training.
Ranked #3 on 3D Object Detection on SUN-RGBD
no code implementations • 31 Mar 2021 • Zichang He, Zheng Zhang
Recently, low-rank tensor methods have been developed to mitigate this issue, but two fundamental challenges remain open: how to automatically determine the tensor rank and how to adaptively pick the informative simulation samples.
72 code implementations • ICCV 2021 • Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo
This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose backbone for computer vision.
Ranked #2 on Image Classification on OmniBenchmark
2 code implementations • 24 Mar 2021 • Yangkun Wang, Jiarui Jin, Weinan Zhang, Yong Yu, Zheng Zhang, David Wipf
Over the past few years, graph neural networks (GNN) and label propagation-based methods have made significant progress in addressing node classification tasks on graphs.
Ranked #1 on Node Property Prediction on ogbn-proteins
1 code implementation • 10 Mar 2021 • Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
Despite the recent success of graph neural networks (GNN), common architectures often exhibit significant limitations, including sensitivity to oversmoothing, long-range dependencies, and spurious edges, e. g., as can occur as a result of graph heterophily or adversarial attacks.
no code implementations • 16 Feb 2021 • Wei Huang, Oliver Linton, Zheng Zhang
We propose a general framework for the specification testing of continuous treatment effect models.
1 code implementation • 10 Feb 2021 • Matthew Wicker, Luca Laurenti, Andrea Patane, Zhoutong Chen, Zheng Zhang, Marta Kwiatkowska
We consider adversarial training of deep neural networks through the lens of Bayesian learning, and present a principled framework for adversarial training of Bayesian Neural Networks (BNNs) with certifiable guarantees.
1 code implementation • ICLR 2021 • Zhuotong Chen, Qianxiao Li, Zheng Zhang
We connect the robustness of neural networks with optimal control using the geometrical information of underlying data to design the control objective.
1 code implementation • ICCV 2021 • Zhi Chen, Yadan Luo, Ruihong Qiu, Sen Wang, Zi Huang, Jingjing Li, Zheng Zhang
Generalized zero-shot learning (GZSL) aims to classify samples under the assumption that some classes are not observable during training.
no code implementations • 9 Jan 2021 • Zhi Chen, Zi Huang, Jingjing Li, Zheng Zhang
To address these issues, in this paper, we propose a novel framework that leverages dual variational autoencoders with a triplet loss to learn discriminative latent features and applies the entropy-based calibration to minimize the uncertainty in the overlapped area between the seen and unseen classes.
no code implementations • ICCVW 2021 • Zhuliang Yao, Yue Cao, Yutong Lin, Ze Liu, Zheng Zhang, Han Hu
Transformer-based vision architectures have attracted great attention because of the strong performance over the convolutional neural networks (CNNs).
no code implementations • 1 Jan 2021 • Jiarui Jin, Sijin Zhou, Weinan Zhang, Rasool Fakoor, David Wipf, Tong He, Yong Yu, Zheng Zhang, Alex Smola
In reinforcement learning, a map with states and transitions built based on historical trajectories is often helpful in exploration and exploitation.
no code implementations • 1 Jan 2021 • Xinyang Zhang, Zheng Zhang, Ting Wang
One intriguing property of deep neural networks (DNNs) is their vulnerability to adversarial perturbations.
no code implementations • 23 Dec 2020 • Zichang He, Bo Zhao, Zheng Zhang
In this paper, we introduce an active low-rank tensor model for fast MR imaging.
1 code implementation • 16 Dec 2020 • Ren Pang, Zheng Zhang, Xiangshan Gao, Zhaohan Xi, Shouling Ji, Peng Cheng, Xiapu Luo, Ting Wang
To bridge this gap, we design and implement TROJANZOO, the first open-source platform for evaluating neural backdoor attacks/defenses in a unified, holistic, and practical manner.
1 code implementation • 14 Dec 2020 • Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf
Cycle-consistent training is widely used for jointly learning a forward and inverse mapping between two domains of interest without the cumbersome requirement of collecting matched pairs within each domain.
1 code implementation • COLING 2020 • Zhijing Jin, Qipeng Guo, Xipeng Qiu, Zheng Zhang
With a human-annotated test set, we provide this new benchmark dataset for future research on unsupervised text generation from knowledge graphs.
Ranked #1 on Unsupervised KG-to-Text Generation on GenWiki (Fine)
1 code implementation • 25 Nov 2020 • Jiarui Jin, Kounianhua Du, Weinan Zhang, Jiarui Qin, Yuchen Fang, Yong Yu, Zheng Zhang, Alexander J. Smola
Heterogeneous information network (HIN) has been widely used to characterize entities of various types and their complex relations.
7 code implementations • CVPR 2021 • Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, Han Hu
We argue that the power of contrastive learning has yet to be fully unleashed, as current methods are trained only on instance-level pretext tasks, leading to representations that may be sub-optimal for downstream tasks requiring dense pixel predictions.
no code implementations • 12 Nov 2020 • Chulaka Gunasekara, Seokhwan Kim, Luis Fernando D'Haro, Abhinav Rastogi, Yun-Nung Chen, Mihail Eric, Behnam Hedayatnia, Karthik Gopalakrishnan, Yang Liu, Chao-Wei Huang, Dilek Hakkani-Tür, Jinchao Li, Qi Zhu, Lingxiao Luo, Lars Liden, Kaili Huang, Shahin Shayandeh, Runze Liang, Baolin Peng, Zheng Zhang, Swadheen Shukla, Minlie Huang, Jianfeng Gao, Shikib Mehri, Yulan Feng, Carla Gordon, Seyed Hossein Alavi, David Traum, Maxine Eskenazi, Ahmad Beirami, Eunjoon, Cho, Paul A. Crook, Ankita De, Alborz Geramifard, Satwik Kottur, Seungwhan Moon, Shivani Poddar, Rajen Subba
Interactive evaluation of dialog, and 4.
1 code implementation • 17 Oct 2020 • Cole Hawkins, Xing Liu, Zheng Zhang
This paper presents a novel end-to-end framework for low-rank tensorized training of neural networks.
1 code implementation • 11 Oct 2020 • Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis
To minimize the overheads associated with distributed computations, DistDGL uses a high-quality and light-weight min-cut graph partitioning algorithm along with multiple balancing constraints.
1 code implementation • COLING 2020 • Tianxiang Sun, Yunfan Shao, Xipeng Qiu, Qipeng Guo, Yaru Hu, Xuanjing Huang, Zheng Zhang
With the emerging branch of incorporating factual knowledge into pre-trained language models such as BERT, most existing models consider shallow, static, and separately pre-trained entity embeddings, which limits the performance gains of these models.
no code implementations • 15 Sep 2020 • Xiaohong Chen, Ying Liu, Shujie Ma, Zheng Zhang
This paper considers a generalized optimization framework for efficient estimation of general treatment effects using artificial neural networks (ANNs) to approximate the unknown nuisance function of growing-dimensional confounders.
no code implementations • 8 Sep 2020 • Yan Zhang, Zhao Zhang, Yang Wang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang
Nonnegative matrix factorization is usually powerful for learning the "shallow" parts-based representation, but it clearly fails to discover deep hierarchical information within both the basis and representation spaces.
no code implementations • 26 Aug 2020 • Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
FeatGraph provides a flexible programming interface to express diverse GNN models by composing coarse-grained sparse templates with fine-grained user-defined functions (UDFs) on each vertex/edge.
1 code implementation • 1 Aug 2020 • Xinyang Zhang, Zheng Zhang, Shouling Ji, Ting Wang
Recent years have witnessed the emergence of a new paradigm of building natural language processing (NLP) systems: general-purpose, pre-trained language models (LMs) are composed with simple downstream models and fine-tuned for a variety of NLP tasks.
1 code implementation • 31 Jul 2020 • Yadan Luo, Zi Huang, Zijian Wang, Zheng Zhang, Mahsa Baktashmotlagh
To further enhance the model capacity and testify the robustness of the proposed architecture on difficult transfer tasks, we extend our model to work in a semi-supervised setting using an additional video-level bipartite graph.
Ranked #2 on Domain Adaptation on HMDB --> UCF (full)
1 code implementation • NeurIPS 2020 • Yihong Chen, Zheng Zhang, Yue Cao, Li-Wei Wang, Stephen Lin, Han Hu
Though RepPoints provides high performance, we find that its heavy reliance on regression for object localization leaves room for improvement.
Ranked #27 on Object Detection on COCO-O
1 code implementation • ECCV 2020 • Ze Liu, Han Hu, Yue Cao, Zheng Zhang, Xin Tong
Our investigation reveals that despite the different designs of these operators, all of these operators make surprisingly similar contributions to the network performance under the same network input and feature numbers and result in the state-of-the-art accuracy on standard benchmarks.
Ranked #4 on 3D Semantic Segmentation on PartNet