Search Results for author: Xiao Wang

Found 197 papers, 110 papers with code

RoCoIns: Enhancing Robustness of Large Language Models through Code-Style Instructions

no code implementations26 Feb 2024 Yuansen Zhang, Xiao Wang, Zhiheng Xi, Han Xia, Tao Gui, Qi Zhang, Xuanjing Huang

In this paper, drawing inspiration from recent works that LLMs are sensitive to the design of the instructions, we utilize instructions in code style, which are more structural and less ambiguous, to replace typically natural language instructions.

CodeChameleon: Personalized Encryption Framework for Jailbreaking Large Language Models

no code implementations26 Feb 2024 Huijie Lv, Xiao Wang, Yuansen Zhang, Caishuang Huang, Shihan Dou, Junjie Ye, Tao Gui, Qi Zhang, Xuanjing Huang

Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs).

Code Completion Response Generation

Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning

1 code implementation8 Feb 2024 Zhiheng Xi, Wenxiang Chen, Boyang Hong, Senjie Jin, Rui Zheng, wei he, Yiwen Ding, Shichun Liu, Xin Guo, Junzhe Wang, Honglin Guo, Wei Shen, Xiaoran Fan, Yuhao Zhou, Shihan Dou, Xiao Wang, Xinbo Zhang, Peng Sun, Tao Gui, Qi Zhang, Xuanjing Huang

In this paper, we propose R$^3$: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the benefits of process supervision for large language models.

GSM8K reinforcement-learning +1

A Lightweight Inception Boosted U-Net Neural Network for Routability Prediction

1 code implementation7 Feb 2024 Hailiang Li, Yan Huo, Yan Wang, Xu Yang, Miaohui Hao, Xiao Wang

As the modern CPU, GPU, and NPU chip design complexity and transistor counts keep increasing, and with the relentless shrinking of semiconductor technology nodes to nearly 1 nanometer, the placement and routing have gradually become the two most pivotal processes in modern very-large-scale-integrated (VLSI) circuit back-end design.

Avg SSIM

Federated Learning with New Knowledge: Fundamentals, Advances, and Futures

1 code implementation3 Feb 2024 Lixu Wang, Yang Zhao, Jiahua Dong, Ating Yin, Qinbin Li, Xiao Wang, Dusit Niyato, Qi Zhu

Federated Learning (FL) is a privacy-preserving distributed learning approach that is rapidly developing in an era where privacy protection is increasingly valued.

Federated Learning Privacy Preserving

Graph Fairness Learning under Distribution Shifts

no code implementations30 Jan 2024 Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi

Recently, there has been an increasing interest in ensuring fairness on GNNs, but all of them are under the assumption that the training and testing data are under the same distribution, i. e., training data and testing data are from the same graph.

Fairness

Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback

1 code implementation21 Jan 2024 Songyang Gao, Qiming Ge, Wei Shen, Shihan Dou, Junjie Ye, Xiao Wang, Rui Zheng, Yicheng Zou, Zhi Chen, Hang Yan, Qi Zhang, Dahua Lin

This reliance limits the applicability of RLHF and hinders the development of professional assistants tailored to diverse human preferences.

Uncertainty-aware Bridge based Mobile-Former Network for Event-based Pattern Recognition

1 code implementation20 Jan 2024 Haoxiang Yang, Chengguo Yuan, Yabin Zhu, Lan Chen, Xiao Wang, Jin Tang

The mainstream human activity recognition (HAR) algorithms are developed based on RGB cameras, which are easily influenced by low-quality images (e. g., low illumination, motion blur).

Human Activity Recognition

CRSOT: Cross-Resolution Object Tracking using Unaligned Frame and Event Cameras

1 code implementation5 Jan 2024 Yabin Zhu, Xiao Wang, Chenglong Li, Bo Jiang, Lin Zhu, Zhixiang Huang, Yonghong Tian, Jin Tang

In this work, we formally propose the task of object tracking using unaligned neuromorphic and visible cameras.

Object Tracking

Federated Continual Novel Class Learning

no code implementations21 Dec 2023 Lixu Wang, Chenxi Liu, Junfeng Guo, Jiahua Dong, Xiao Wang, Heng Huang, Qi Zhu

In a privacy-focused era, Federated Learning (FL) has emerged as a promising machine learning technique.

Federated Learning Novel Class Discovery +1

GenoCraft: A Comprehensive, User-Friendly Web-Based Platform for High-Throughput Omics Data Analysis and Visualization

1 code implementation21 Dec 2023 Yingzhou Lu, Minjie Shen, Yue Zhao, Chenhao Li, Fan Meng, Xiao Wang, David Herrington, Yue Wang, Tim Fu, Capucine van Rechem

With GenoCraft, researchers and data scientists have access to an array of cutting-edge bioinformatics tools under a user-friendly interface, making it a valuable resource for managing and analyzing large-scale omics data.

Optimizing Distributed Training on Frontier for Large Language Models

no code implementations20 Dec 2023 Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash

For the training of the 175 Billion parameter model and the 1 Trillion parameter model, we achieved $100\%$ weak scaling efficiency on 1024 and 3072 MI250X GPUs, respectively.

Computational Efficiency

Unleashing the Power of CNN and Transformer for Balanced RGB-Event Video Recognition

1 code implementation18 Dec 2023 Xiao Wang, Yao Rong, Shiao Wang, Yuan Chen, Zhe Wu, Bo Jiang, Yonghong Tian, Jin Tang

It is intuitive to combine them for high-performance RGB-Event based video recognition, however, existing works fail to achieve a good balance between the accuracy and model parameters, as shown in Fig.~\ref{firstimage}.

Video Recognition

Pedestrian Attribute Recognition via CLIP based Prompt Vision-Language Fusion

2 code implementations17 Dec 2023 Xiao Wang, Jiandong Jin, Chenglong Li, Jin Tang, Cheng Zhang, Wei Wang

In this paper, we formulate PAR as a vision-language fusion problem and fully exploit the relations between pedestrian images and attribute labels.

Attribute Contrastive Learning +2

Structural Information Guided Multimodal Pre-training for Vehicle-centric Perception

1 code implementation15 Dec 2023 Xiao Wang, Wentao Wu, Chenglong Li, Zhicheng Zhao, Zhe Chen, Yukai Shi, Jin Tang

To address this issue, we propose a novel vehicle-centric pre-training framework called VehicleMAE, which incorporates the structural information including the spatial structure from vehicle profile information and the semantic structure from informative high-level natural language descriptions for effective masked vehicle appearance reconstruction.

LoRAMoE: Revolutionizing Mixture of Experts for Maintaining World Knowledge in Language Model Alignment

no code implementations15 Dec 2023 Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Jun Zhao, Wei Shen, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Xiaoran Fan, ShiLiang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang

When the models are required to align with a broader range of downstream tasks, or there is a desire to notably improve the performance on a specific task, a substantial increase in fine-tuning data often emerges as the solution.

Language Modelling Multi-Task Learning +1

A Generalized Neural Diffusion Framework on Graphs

no code implementations14 Dec 2023 Yibo Li, Xiao Wang, Hongrui Liu, Chuan Shi

In this paper, we propose a general diffusion equation framework with the fidelity term, which formally establishes the relationship between the diffusion process with more GNNs.

SequencePAR: Understanding Pedestrian Attributes via A Sequence Generation Paradigm

2 code implementations4 Dec 2023 Jiandong Jin, Xiao Wang, Chenglong Li, Lili Huang, Jin Tang

Then, a Transformer decoder is proposed to generate the human attributes by incorporating the visual features and attribute query tokens.

Attribute Multi-Task Learning +1

RTQ: Rethinking Video-language Understanding Based on Image-text Model

1 code implementation1 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.

Semantic-Aware Frame-Event Fusion based Pattern Recognition via Large Vision-Language Models

1 code implementation30 Nov 2023 Dong Li, Jiandong Jin, Yuhao Zhang, Yanlin Zhong, Yaoyang Wu, Lan Chen, Xiao Wang, Bin Luo

Current methods typically employ backbone networks to individually extract the features of RGB frames and event streams, and subsequently fuse these features for pattern recognition.

Language Modelling Prompt Engineering

Ultra-Long Sequence Distributed Transformer

no code implementations4 Nov 2023 Xiao Wang, Isaac Lyngaas, Aristeidis Tsaris, Peng Chen, Sajal Dash, Mayanka Chandra Shekar, Tao Luo, Hong-Jun Yoon, Mohamed Wahib, John Gouley

This paper presents a novel and efficient distributed training method, the Long Short-Sequence Transformer (LSS Transformer), for training transformer with long sequences.

Orthogonal Subspace Learning for Language Model Continual Learning

1 code implementation22 Oct 2023 Xiao Wang, Tianze Chen, Qiming Ge, Han Xia, Rong Bao, Rui Zheng, Qi Zhang, Tao Gui, Xuanjing Huang

In this paper, we propose orthogonal low-rank adaptation (O-LoRA), a simple and efficient approach for continual learning in language models, effectively mitigating catastrophic forgetting while learning new tasks.

Continual Learning Language Modelling

VcT: Visual change Transformer for Remote Sensing Image Change Detection

1 code implementation17 Oct 2023 Bo Jiang, Zitian Wang, Xixi Wang, Ziyan Zhang, Lan Chen, Xiao Wang, Bin Luo

Then, each pixel of feature map is regarded as a graph node and the graph neural network is proposed to model the structured information for coarse change map prediction.

Change Detection Representation Learning

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies

no code implementations6 Oct 2023 Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi Hanson, Thomas E Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin Aji, Angela Dalton, Michael Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences.

Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models

no code implementations4 Oct 2023 Xianjun Yang, Xiao Wang, Qi Zhang, Linda Petzold, William Yang Wang, Xun Zhao, Dahua Lin

This study serves as a clarion call for a collective effort to overhaul and fortify the safety of open-source LLMs against malicious attackers.

A stochastic block model for community detection in attributed networks

no code implementations31 Aug 2023 Xiao Wang, Fang Dai, Wenyan Guo, Junfeng Wang

Therefore, a stochastic block model that integrates betweenness centrality and clustering coefficient of nodes for community detection in attributed networks, named BCSBM, is proposed in this paper.

Clustering Community Detection +1

Learning Bottleneck Transformer for Event Image-Voxel Feature Fusion based Classification

1 code implementation23 Aug 2023 Chengguo Yuan, Yu Jin, Zongzhen Wu, Fanting Wei, Yangzirui Wang, Lan Chen, Xiao Wang

Additionally, a bottleneck Transformer is introduced to facilitate the fusion of the dual-stream information.

Temporal Sentence Grounding in Streaming Videos

1 code implementation14 Aug 2023 Tian Gan, Xiao Wang, Yan Sun, Jianlong Wu, Qingpei Guo, Liqiang Nie

The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query.

Sentence Temporal Sentence Grounding

High-performance Data Management for Whole Slide Image Analysis in Digital Pathology

1 code implementation10 Aug 2023 Haoju Leng, Ruining Deng, Shunxing Bao, Dazheng Fang, Bryan A. Millis, Yucheng Tang, Haichun Yang, Xiao Wang, Yifan Peng, Lipeng Wan, Yuankai Huo

The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario ("CPU scenario"), and (2) a GPU-based deep learning framework scenario ("GPU scenario").

Management whole slide images

SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition

1 code implementation8 Aug 2023 Xiao Wang, Zongzhen Wu, Yao Rong, Lin Zhu, Bo Jiang, Jin Tang, Yonghong Tian

Secondly, they adopt either Spiking Neural Networks (SNN) for energy-efficient recognition with suboptimal results, or Artificial Neural Networks (ANN) for energy-intensive, high-performance recognition.

Generative Query Reformulation for Effective Adhoc Search

no code implementations1 Aug 2023 Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis

GenQR directly reformulates the user's input query, while GenPRF provides additional context for the query by making use of pseudo-relevance feedback information.

Information Retrieval Retrieval

DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization

1 code implementation27 Jun 2023 Songyang Gao, Shihan Dou, Yan Liu, Xiao Wang, Qi Zhang, Zhongyu Wei, Jin Ma, Ying Shan

Adversarial training is one of the best-performing methods in improving the robustness of deep language models.

Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition

1 code implementation8 Jun 2023 Bo Jiang, Chengguo Yuan, Xiao Wang, Zhimin Bao, Lin Zhu, Yonghong Tian, Jin Tang

To address these issues, we propose a novel dual point-voxel absorbing graph representation learning for event stream data representation.

Event data classification Graph Representation Learning

AMatFormer: Efficient Feature Matching via Anchor Matching Transformer

no code implementations30 May 2023 Bo Jiang, Shuxian Luo, Xiao Wang, Chuanfu Li, Jin Tang

Second, AMatFormer adopts a shared FFN module to further embed the features of two images into the common domain and thus learn the consensus feature representations for the matching problem.

A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition

1 code implementation21 May 2023 Limao Xiong, Jie zhou, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan

Particularly, we propose a Confidence-based Partial Label Learning (CPLL) method to integrate the prior confidence (given by annotators) and posterior confidences (learned by models) for crowd-annotated NER.

named-entity-recognition Named Entity Recognition +2

ReGeneration Learning of Diffusion Models with Rich Prompts for Zero-Shot Image Translation

no code implementations8 May 2023 Yupei Lin, Sen Zhang, Xiaojun Yang, Xiao Wang, Yukai Shi

To ensure consistent preservation of the shape during image editing, we propose cross-attention guidance based on regeneration learning.

Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network

no code implementations24 Apr 2023 Nian Liu, Xiao Wang, Hui Han, Chuan Shi

Specifically, two views of a HIN (network schema and meta-path views) are proposed to learn node embeddings, so as to capture both of local and high-order structures simultaneously.

Contrastive Learning

Learning CLIP Guided Visual-Text Fusion Transformer for Video-based Pedestrian Attribute Recognition

1 code implementation20 Apr 2023 Jun Zhu, Jiandong Jin, Zihan Yang, Xiaohao Wu, Xiao Wang

The averaged visual tokens and text tokens are concatenated and fed into a fusion Transformer for multi-modal interactive learning.

Attribute Pedestrian Attribute Recognition +1

Curricular Object Manipulation in LiDAR-based Object Detection

1 code implementation CVPR 2023 Ziyue Zhu, Qiang Meng, Xiao Wang, Ke Wang, Liujiang Yan, Jian Yang

For the loss design, we propose the COMLoss to dynamically predict object-level difficulties and emphasize objects of different difficulties based on training stages.

3D Object Detection Object +1

Efficient Multimodal Sampling via Tempered Distribution Flow

1 code implementation8 Apr 2023 Yixuan Qiu, Xiao Wang

Sampling from high-dimensional distributions is a fundamental problem in statistical research and practice.

Image Generation

RGBT Tracking via Progressive Fusion Transformer with Dynamically Guided Learning

no code implementations26 Mar 2023 Yabin Zhu, Chenglong Li, Xiao Wang, Jin Tang, Zhixiang Huang

In addition, existing learning methods of RGBT trackers either fuse multimodal features into one for final classification, or exploit the relationship between unimodal branches and fused branch through a competitive learning strategy.

Micro-video Tagging via Jointly Modeling Social Influence and Tag Relation

1 code implementation15 Mar 2023 Xiao Wang, Tian Gan, Yinwei Wei, Jianlong Wu, Dai Meng, Liqiang Nie

Existing methods mostly focus on analyzing video content, neglecting users' social influence and tag relation.

Link Prediction Relation +3

AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+

1 code implementation14 Mar 2023 Xiao Wang, Ying Wang, Ziwei Xuan, Guo-Jun Qi

A criterion in unsupervised pretraining is the pretext task needs to be sufficiently hard to prevent the transformer encoder from learning trivial low-level features not generalizable well to downstream tasks.

Transfer Learning

Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey

1 code implementation20 Feb 2023 Xiao Wang, Guangyao Chen, Guangwu Qian, Pengcheng Gao, Xiao-Yong Wei, YaoWei Wang, Yonghong Tian, Wen Gao

With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as BERT, ViT, GPT, etc.

A Survey on Spectral Graph Neural Networks

no code implementations11 Feb 2023 Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi

Graph neural networks (GNNs) have attracted considerable attention from the research community.

Graph Representation Learning

Machine Learning for Synthetic Data Generation: A Review

no code implementations8 Feb 2023 Yingzhou Lu, Minjie Shen, Huazheng Wang, Xiao Wang, Capucine van Rechem, Wenqi Wei

In light of these challenges, the concept of synthetic data generation emerges as a promising alternative that allows for data sharing and utilization in ways that real-world data cannot facilitate.

Fairness Synthetic Data Generation

DEJA VU: Continual Model Generalization For Unseen Domains

2 code implementations25 Jan 2023 Chenxi Liu, Lixu Wang, Lingjuan Lyu, Chen Sun, Xiao Wang, Qi Zhu

To overcome these limitations of DA and DG in handling the Unfamiliar Period during continual domain shift, we propose RaTP, a framework that focuses on improving models' target domain generalization (TDG) capability, while also achieving effective target domain adaptation (TDA) capability right after training on certain domains and forgetting alleviation (FA) capability on past domains.

Data Augmentation Domain Generalization

Directed Acyclic Graph Structure Learning from Dynamic Graphs

1 code implementation30 Nov 2022 Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi

In a dynamic graph, we propose to simultaneously estimate contemporaneous relationships and time-lagged interaction relationships between the node features.

Graph structure learning

Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric

2 code implementations20 Nov 2022 Chuanming Tang, Xiao Wang, Ju Huang, Bo Jiang, Lin Zhu, Jianlin Zhang, YaoWei Wang, Yonghong Tian

In this paper, we propose a single-stage backbone network for Color-Event Unified Tracking (CEUTrack), which achieves the above functions simultaneously.

Object Localization Object Tracking

Rethinking Batch Sample Relationships for Data Representation: A Batch-Graph Transformer based Approach

no code implementations19 Nov 2022 Xixi Wang, Bo Jiang, Xiao Wang, Bin Luo

(1) It employs a flexible graph model, termed Batch Graph to jointly encode the visual and semantic relationships of samples within each mini-batch.

Metric Learning

HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors

2 code implementations17 Nov 2022 Xiao Wang, Zongzhen Wu, Bo Jiang, Zhimin Bao, Lin Zhu, Guoqi Li, YaoWei Wang, Yonghong Tian

The main streams of human activity recognition (HAR) algorithms are developed based on RGB cameras which are suffered from illumination, fast motion, privacy-preserving, and large energy consumption.

Activity Prediction Human Activity Recognition +1

Provably Safe Reinforcement Learning via Action Projection using Reachability Analysis and Polynomial Zonotopes

no code implementations19 Oct 2022 Niklas Kochdumper, Hanna Krasowski, Xiao Wang, Stanley Bak, Matthias Althoff

While reinforcement learning produces very promising results for many applications, its main disadvantage is the lack of safety guarantees, which prevents its use in safety-critical systems.

reinforcement-learning Reinforcement Learning (RL) +1

Uncovering the Structural Fairness in Graph Contrastive Learning

1 code implementation6 Oct 2022 Ruijia Wang, Xiao Wang, Chuan Shi, Le Song

Recent studies show that graph convolutional network (GCN) often performs worse for low-degree nodes, exhibiting the so-called structural unfairness for graphs with long-tailed degree distributions prevalent in the real world.

Contrastive Learning Fairness

Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum

1 code implementation5 Oct 2022 Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei

Then we theoretically prove that GCL is able to learn the invariance information by contrastive invariance theorem, together with our GAME rule, for the first time, we uncover that the learned representations by GCL essentially encode the low-frequency information, which explains why GCL works.

Contrastive Learning

Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure

1 code implementation28 Sep 2022 Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang

However, by presenting a graph classification investigation on the training graphs with severe bias, surprisingly, we discover that GNNs always tend to explore the spurious correlations to make decision, even if the causal correlation always exists.

counterfactual Graph Classification

See Finer, See More: Implicit Modality Alignment for Text-based Person Retrieval

1 code implementation18 Aug 2022 Xiujun Shu, Wei Wen, Haoqian Wu, Keyu Chen, Yiran Song, Ruizhi Qiao, Bo Ren, Xiao Wang

To explore the fine-grained alignment, we further propose two implicit semantic alignment paradigms: multi-level alignment (MLA) and bidirectional mask modeling (BMM).

Person Retrieval Retrieval +3

Learning Spatial-Frequency Transformer for Visual Object Tracking

2 code implementations18 Aug 2022 Chuanming Tang, Xiao Wang, Yuanchao Bai, Zhe Wu, Jianlin Zhang, YongMei Huang

To handle these issues, in this paper, we propose a unified Spatial-Frequency Transformer that models the Gaussian spatial Prior and High-frequency emphasis Attention (GPHA) simultaneously.

Object Visual Object Tracking

Criteria Comparative Learning for Real-scene Image Super-Resolution

2 code implementations26 Jul 2022 Yukai Shi, Hao Li, Sen Zhang, Zhijing Yang, Xiao Wang

Inspired by the observation that the contrastive relationship could also exist between the criteria, in this work, we propose a novel training paradigm for RealSR, named Criteria Comparative Learning (Cria-CL), by developing contrastive losses defined on criteria instead of image patches.

Contrastive Learning Image Super-Resolution +1

SPAIC: A Spike-based Artificial Intelligence Computing Framework

1 code implementation26 Jul 2022 Chaofei Hong, Mengwen Yuan, Mengxiao Zhang, Xiao Wang, Chegnjun Zhang, Jiaxin Wang, Gang Pan, Zhaohui Wu, Huajin Tang

In this work, we present a Python based spiking neural network (SNN) simulation and training framework, aka SPAIC that aims to support brain-inspired model and algorithm researches integrated with features from both deep learning and neuroscience.

Prompt-based Learning for Unpaired Image Captioning

no code implementations26 May 2022 Peipei Zhu, Xiao Wang, Lin Zhu, Zhenglong Sun, Weishi Zheng, YaoWei Wang, Changwen Chen

Inspired by the success of Vision-Language Pre-Trained Models (VL-PTMs) in this research, we attempt to infer the cross-domain cue information about a given image from the large VL-PTMs for the UIC task.

Image Captioning Question Answering +2

Robust Sensible Adversarial Learning of Deep Neural Networks for Image Classification

1 code implementation20 May 2022 Jungeum Kim, Xiao Wang

Specifically, we define a sensible adversary which is useful for learning a robust model while keeping high natural accuracy.

Image Classification Object Recognition

Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search

1 code implementation19 May 2022 Xiao Wang, Zhe Chen, Bo Jiang, Jin Tang, Bin Luo, DaCheng Tao

To track the target in a video, current visual trackers usually adopt greedy search for target object localization in each frame, that is, the candidate region with the maximum response score will be selected as the tracking result of each frame.

Decision Making Image Captioning +5

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

no code implementations12 May 2022 Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob Hinkle

In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles.

Accelerated Multiplicative Weights Update Avoids Saddle Points almost always

no code implementations25 Apr 2022 Yi Feng, Ioannis Panageas, Xiao Wang

We consider non-convex optimization problems with constraint that is a product of simplices.

On the Importance of Asymmetry for Siamese Representation Learning

1 code implementation CVPR 2022 Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen

Many recent self-supervised frameworks for visual representation learning are based on certain forms of Siamese networks.

Representation Learning

Federated Class-Incremental Learning

1 code implementation CVPR 2022 Jiahua Dong, Lixu Wang, Zhen Fang, Gan Sun, Shichao Xu, Xiao Wang, Qi Zhu

It makes the global model suffer from significant catastrophic forgetting on old classes in real-world scenarios, where local clients often collect new classes continuously and have very limited storage memory to store old classes.

Class Incremental Learning Federated Learning +1

Unpaired Image Captioning by Image-level Weakly-Supervised Visual Concept Recognition

no code implementations7 Mar 2022 Peipei Zhu, Xiao Wang, Yong Luo, Zhenglong Sun, Wei-Shi Zheng, YaoWei Wang, Changwen Chen

The image-level labels are utilized to train a weakly-supervised object recognition model to extract object information (e. g., instance) in an image, and the extracted instances are adopted to infer the relationships among different objects based on an enhanced graph neural network (GNN).

Image Captioning Object +1

Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network

1 code implementation18 Feb 2022 Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi

Heterogeneous Graph Neural Network (HGNN) has been successfully employed in various tasks, but we cannot accurately know the importance of different design dimensions of HGNNs due to diverse architectures and applied scenarios.

Tiny Object Tracking: A Large-scale Dataset and A Baseline

1 code implementation11 Feb 2022 Yabin Zhu, Chenglong Li, Yao Liu, Xiao Wang, Jin Tang, Bin Luo, Zhixiang Huang

Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation.

Attribute Knowledge Distillation +4

Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift

1 code implementation27 Jan 2022 Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou

To this end, in this paper, we propose a novel Distribution Recovered Graph Self-Training framework (DR-GST), which could recover the distribution of the original labeled dataset.

Variational Inference

Event-based Video Reconstruction via Potential-assisted Spiking Neural Network

1 code implementation CVPR 2022 Lin Zhu, Xiao Wang, Yi Chang, Jianing Li, Tiejun Huang, Yonghong Tian

We propose a novel Event-based Video reconstruction framework based on a fully Spiking Neural Network (EVSNN), which utilizes Leaky-Integrate-and-Fire (LIF) neuron and Membrane Potential (MP) neuron.

Computational Efficiency Event-Based Video Reconstruction +2

Debiased Graph Neural Networks with Agnostic Label Selection Bias

no code implementations19 Jan 2022 Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang

Then to remove the bias in GNN estimation, we propose a novel Debiased Graph Neural Networks (DGNN) with a differentiated decorrelation regularizer.

Selection bias Test

Compact Graph Structure Learning via Mutual Information Compression

2 code implementations14 Jan 2022 Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi

Furthermore, we maintain the performance of estimated views and the final view and reduce the mutual information of every two views.

Graph structure learning

Universal Graph Convolutional Networks

1 code implementation NeurIPS 2021 Di Jin, Zhizhi Yu, Cuiying Huo, Rui Wang, Xiao Wang, Dongxiao He, Jiawei Han

So can we reasonably utilize these segmentation rules to design a universal propagation mechanism independent of the network structural assumption?

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs

1 code implementation20 Nov 2021 Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang

Graph Neural Networks (GNNs) are proposed without considering the agnostic distribution shifts between training and testing graphs, inducing the degeneration of the generalization ability of GNNs on Out-Of-Distribution (OOD) settings.

Causal Inference

LiT: Zero-Shot Transfer with Locked-image text Tuning

4 code implementations CVPR 2022 Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer

This paper presents contrastive-tuning, a simple method employing contrastive training to align image and text models while still taking advantage of their pre-training.

Image Classification Retrieval +3

CoSeg: Cognitively Inspired Unsupervised Generic Event Segmentation

1 code implementation30 Sep 2021 Xiao Wang, Jingen Liu, Tao Mei, Jiebo Luo

Unlike the mainstream clustering-based methods, our framework exploits a transformer-based feature reconstruction scheme to detect event boundary by reconstruction errors.

Boundary Detection Event Segmentation +1

Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration

2 code implementations NeurIPS 2021 Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang

Specifically, we first verify that the confidence distribution in a graph has homophily property, and this finding inspires us to design a calibration GNN model (CaGCN) to learn the calibration function.

Inferential Wasserstein Generative Adversarial Networks

no code implementations13 Sep 2021 Yao Chen, Qingyi Gao, Xiao Wang

The Wasserstein GAN (WGAN) leverages the Wasserstein distance to avoid the caveats in the minmax two-player training of GANs but has other defects such as mode collapse and lack of metric to detect the convergence.

Constants of Motion: The Antidote to Chaos in Optimization and Game Dynamics

no code implementations8 Sep 2021 Georgios Piliouras, Xiao Wang

Several recent works in online optimization and game dynamics have established strong negative complexity results including the formal emergence of instability and chaos even in small such settings, e. g., $2\times 2$ games.

VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows

2 code implementations11 Aug 2021 Xiao Wang, Jianing Li, Lin Zhu, Zhipeng Zhang, Zhe Chen, Xin Li, YaoWei Wang, Yonghong Tian, Feng Wu

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency.

Object Tracking

Learn to Match: Automatic Matching Network Design for Visual Tracking

1 code implementation ICCV 2021 Zhipeng Zhang, Yihao Liu, Xiao Wang, Bing Li, Weiming Hu

Siamese tracking has achieved groundbreaking performance in recent years, where the essence is the efficient matching operator cross-correlation and its variants.

Visual Tracking

MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking

2 code implementations22 Jul 2021 Xiao Wang, Xiujun Shu, Shiliang Zhang, Bo Jiang, YaoWei Wang, Yonghong Tian, Feng Wu

The visible and thermal filters will be used to conduct a dynamic convolutional operation on their corresponding input feature maps respectively.

Rgb-T Tracking

Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval

3 code implementations21 Jun 2021 Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis

In particular, based on the pseudo-relevant set of documents identified using a first-pass dense retrieval, we extract representative feedback embeddings (using KMeans clustering) -- while ensuring that these embeddings discriminate among passages (based on IDF) -- which are then added to the query representation.

Information Retrieval Passage Ranking +2

Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization

1 code implementation ICLR 2022 Lixu Wang, Shichao Xu, Ruiqi Xu, Xiao Wang, Qi Zhu

Our NTL-based authorization approach instead provides data-centric protection, which we call applicability authorization, by significantly degrading the performance of the model on unauthorized data.

Tracking by Joint Local and Global Search: A Target-aware Attention based Approach

1 code implementation9 Jun 2021 Xiao Wang, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu

In this paper, we propose a novel and general target-aware attention mechanism (termed TANet) and integrate it with tracking-by-detection framework to conduct joint local and global search for robust tracking.

Object Object Tracking

Large-Scale Spatio-Temporal Person Re-identification: Algorithms and Benchmark

2 code implementations31 May 2021 Xiujun Shu, Xiao Wang, Xianghao Zang, Shiliang Zhang, Yuanqi Chen, Ge Li, Qi Tian

We also verified that models pre-trained on LaST can generalize well on existing datasets with short-term and cloth-changing scenarios.

Person Re-Identification

Guidance and Teaching Network for Video Salient Object Detection

no code implementations21 May 2021 Yingxia Jiao, Xiao Wang, Yu-Cheng Chou, Shouyuan Yang, Ge-Peng Ji, Rong Zhu, Ge Gao

Owing to the difficulties of mining spatial-temporal cues, the existing approaches for video salient object detection (VSOD) are limited in understanding complex and noisy scenarios, and often fail in inferring prominent objects.

Object object-detection +2

Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning

3 code implementations19 May 2021 Xiao Wang, Nian Liu, Hui Han, Chuan Shi

Then the cross-view contrastive learning, as well as a view mask mechanism, is proposed, which is able to extract the positive and negative embeddings from two views.

Contrastive Learning

Substitutional Neural Image Compression

no code implementations16 May 2021 Xiao Wang, Wei Jiang, Wei Wang, Shan Liu, Brian Kulis, Peter Chin

The key idea is to replace the image to be compressed with a substitutional one that outperforms the original one in a desired way.

Image Compression

High-Robustness, Low-Transferability Fingerprinting of Neural Networks

no code implementations14 May 2021 Siyue Wang, Xiao Wang, Pin-Yu Chen, Pu Zhao, Xue Lin

This paper proposes Characteristic Examples for effectively fingerprinting deep neural networks, featuring high-robustness to the base model against model pruning as well as low-transferability to unassociated models.

Vocal Bursts Intensity Prediction

Contrastive Learning with Stronger Augmentations

1 code implementation15 Apr 2021 Xiao Wang, Guo-Jun Qi

Thus, we propose a general framework called Contrastive Learning with Stronger Augmentations~(CLSA) to complement current contrastive learning approaches.

Contrastive Learning Representation Learning +3

Lorentzian Graph Convolutional Networks

no code implementations15 Apr 2021 Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song

We also find that the performance of some hyperbolic GCNs can be improved by simply replacing the graph operations with those we defined in this paper.

Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking

1 code implementation30 Mar 2021 Xiao Wang, Zhe Chen, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu

In this paper, we propose to introduce more dynamics by devising a dynamic attention-guided multi-trajectory tracking strategy.

Object Tracking

CaPC Learning: Confidential and Private Collaborative Learning

1 code implementation ICLR 2021 Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang

There is currently no method that enables machine learning in such a setting, where both confidentiality and privacy need to be preserved, to prevent both explicit and implicit sharing of data.

Fairness Federated Learning

Interpreting and Unifying Graph Neural Networks with An Optimization Framework

1 code implementation28 Jan 2021 Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui

Graph Neural Networks (GNNs) have received considerable attention on graph-structured data learning for a wide variety of tasks.

Beyond Low-frequency Information in Graph Convolutional Networks

1 code implementation4 Jan 2021 Deyu Bo, Xiao Wang, Chuan Shi, HuaWei Shen

For a deeper understanding, we theoretically analyze the roles of low-frequency signals and high-frequency signals on learning node representations, which further explains why FAGCN can perform well on different types of networks.

Node Classification on Non-Homophilic (Heterophilic) Graphs

Deep Q Learning from Dynamic Demonstration with Behavioral Cloning

no code implementations1 Jan 2021 Xiaoshuang Li, Junchen Jin, Xiao Wang, Fei-Yue Wang

This study proposes a novel approach integrating deep Q learning from dynamic demonstrations with a behavioral cloning model (DQfDD-BC), which includes a supervised learning technique of instructing a DRL model to enhance its performance.

OpenAI Gym Q-Learning

NeuSpike-Net: High Speed Video Reconstruction via Bio-Inspired Neuromorphic Cameras

no code implementations ICCV 2021 Lin Zhu, Jianing Li, Xiao Wang, Tiejun Huang, Yonghong Tian

In this paper, we propose a NeuSpike-Net to learn both the high dynamic range and high motion sensitivity of DVS and the full texture sampling of spike camera to achieve high-speed and high dynamic image reconstruction.

Image Reconstruction Video Reconstruction +1

A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources

no code implementations30 Nov 2020 Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu

Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension space while preserving the heterogeneous structures and semantics for downstream tasks (e. g., node/graph classification, node clustering, link prediction), has drawn considerable attentions in recent years.

Clustering Graph Classification +5

AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries

2 code implementations CVPR 2021 Qianjiang Hu, Xiao Wang, Wei Hu, Guo-Jun Qi

Contrastive learning relies on constructing a collection of negative examples that are sufficiently hard to discriminate against positive queries when their representations are self-trained.

Contrastive Learning

Cross-Lingual Document Retrieval with Smooth Learning

1 code implementation COLING 2020 Jiapeng Liu, Xiao Zhang, Dan Goldwasser, Xiao Wang

Cross-lingual document search is an information retrieval task in which the queries' language differs from the documents' language.

Information Retrieval Retrieval

Dynamic Fusion based Federated Learning for COVID-19 Detection

no code implementations22 Sep 2020 Weishan Zhang, Tao Zhou, Qinghua Lu, Xiao Wang, Chunsheng Zhu, Haoyun Sun, Zhipeng Wang, Sin Kit Lo, Fei-Yue Wang

To improve communication efficiency and model performance, in this paper, we propose a novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections.

BIG-bench Machine Learning Decision Making +3

Addressing Class Imbalance in Federated Learning

2 code implementations14 Aug 2020 Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu

Our experiments demonstrate the importance of acknowledging class imbalance and taking measures as early as possible in FL training, and the effectiveness of our method in mitigating the impact.

Federated Learning

Deep Reinforced Query Reformulation for Information Retrieval

no code implementations15 Jul 2020 Xiao Wang, Craig Macdonald, Iadh Ounis

Query reformulations have long been a key mechanism to alleviate the vocabulary-mismatch problem in information retrieval, for example by expanding the queries with related query terms or by generating paraphrases of the queries.

Document Ranking Information Retrieval +1

STADB: A Self-Thresholding Attention Guided ADB Network for Person Re-identification

1 code implementation7 Jul 2020 Bo Jiang, Sheng Wang, Xiao Wang, Aihua Zheng

Specifically, STADB first obtains an attention map by channel-wise pooling and returns a drop mask by thresholding the attention map.

Person Re-Identification

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks

no code implementations5 Jul 2020 Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei

We tackle the challenge and propose an adaptive multi-channel graph convolutional networks for semi-supervised classification (AM-GCN).

General Classification

Falsification-Based Robust Adversarial Reinforcement Learning

no code implementations1 Jul 2020 Xiao Wang, Saasha Nair, Matthias Althoff

Robust adversarial RL (RARL) was previously proposed to train an adversarial network that applies disturbances to a system, which improves the robustness in test scenarios.

Autonomous Vehicles Decision Making +3

Decorrelated Clustering with Data Selection Bias

1 code implementation29 Jun 2020 Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang

Most of existing clustering algorithms are proposed without considering the selection bias in data.

Clustering Selection bias