Search Results for author: Kun Wang

Found 164 papers, 58 papers with code

LST-Net: Learning a Convolutional Neural Network with a Learnable Sparse Transform

no code implementations ECCV 2020 Lida Li, Kun Wang, Shuai Li, Xiangchu Feng, Lei Zhang

The 2D convolutional (Conv2d) layer is the fundamental element to a deep convolutional neural network (CNN).

REDEditing: Relationship-Driven Precise Backdoor Poisoning on Text-to-Image Diffusion Models

no code implementations20 Apr 2025 Chongye Guo, Jinhu Fu, Junfeng Fang, Kun Wang, Guorui Feng

In this work, we establish the principles for backdoor attacks based on model editing, and propose a relationship-driven precise backdoor poisoning method, REDEditing.

ARise: Towards Knowledge-Augmented Reasoning via Risk-Adaptive Search

no code implementations15 Apr 2025 Yize Zhang, Tianshu Wang, Sirui Chen, Kun Wang, Xingyu Zeng, Hongyu Lin, Xianpei Han, Le Sun, Chaochao Lu

Large language models (LLMs) have demonstrated impressive capabilities and are receiving increasing attention to enhance their reasoning through scaling test--time compute.

RAG World Knowledge

SafeMLRM: Demystifying Safety in Multi-modal Large Reasoning Models

no code implementations9 Apr 2025 Junfeng Fang, Yukai Wang, Ruipeng Wang, Zijun Yao, Kun Wang, An Zhang, Xiang Wang, Tat-Seng Chua

The rapid advancement of multi-modal large reasoning models (MLRMs) -- enhanced versions of multimodal language models (MLLMs) equipped with reasoning capabilities -- has revolutionized diverse applications.

Safety Alignment

U2AD: Uncertainty-based Unsupervised Anomaly Detection Framework for Detecting T2 Hyperintensity in MRI Spinal Cord

1 code implementation17 Mar 2025 Qi Zhang, Xiuyuan Chen, Ziyi He, Kun Wang, Lianming Wu, Hongxing Shen, Jianqi Sun

However, existing UAD methods rely on curated normal datasets and their performance frequently deteriorates when applied to clinical datasets due to domain shifts.

Lesion Detection Unsupervised Anomaly Detection

GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editing

1 code implementation13 Mar 2025 Rongyao Fang, Chengqi Duan, Kun Wang, Linjiang Huang, Hao Li, Shilin Yan, Hao Tian, Xingyu Zeng, Rui Zhao, Jifeng Dai, Xihui Liu, Hongsheng Li

We present Generation Chain-of-Thought (GoT), a novel paradigm that enables generation and editing through an explicit language reasoning process before outputting images.

Language Modeling Language Modelling +3

Pathology-Guided AI System for Accurate Segmentation and Diagnosis of Cervical Spondylosis

1 code implementation8 Mar 2025 Qi Zhang, Xiuyuan Chen, Ziyi He, Lianming Wu, Kun Wang, Jianqi Sun, Hongxing Shen

The segmentation is followed by an expert-based diagnostic framework that automates the calculation of critical clinical indicators.

Anatomy Diagnostic +1

HealthiVert-GAN: A Novel Framework of Pseudo-Healthy Vertebral Image Synthesis for Interpretable Compression Fracture Grading

1 code implementation8 Mar 2025 Qi Zhang, Shunan Zhang, Ziqi Zhao, Kun Wang, Jun Xu, Jianqi Sun

Osteoporotic vertebral compression fractures (VCFs) are prevalent in the elderly population, typically assessed on computed tomography (CT) scans by evaluating vertebral height loss.

Computed Tomography (CT) Diagnostic +1

Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders

no code implementations7 Mar 2025 Qijiong Liu, Jieming Zhu, Lu Fan, Kun Wang, Hengchang Hu, Wei Guo, Yong liu, Xiao-Ming Wu

However, a comprehensive benchmark is needed to thoroughly evaluate and compare the recommendation capabilities of LLMs with traditional recommender systems.

Benchmarking Click-Through Rate Prediction +1

AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management

no code implementations6 Mar 2025 Junyuan Mao, Fanci Meng, Yifan Duan, Miao Yu, Xiaojun Jia, Junfeng Fang, Yuxuan Liang, Kun Wang, Qingsong Wen

Large Language Model based multi-agent systems are revolutionizing autonomous communication and collaboration, yet they remain vulnerable to security threats like unauthorized access and data breaches.

Language Modeling Language Modelling +2

Brain Foundation Models: A Survey on Advancements in Neural Signal Processing and Brain Discovery

no code implementations1 Mar 2025 Xinliang Zhou, Chenyu Liu, Zhisheng Chen, Kun Wang, Yi Ding, Ziyu Jia, Qingsong Wen

Brain foundation models (BFMs) have emerged as a transformative paradigm in computational neuroscience, offering a revolutionary framework for processing diverse neural signals across different brain-related tasks.

Survey

InstructAgent: Building User Controllable Recommender via LLM Agent

1 code implementation20 Feb 2025 Wujiang Xu, Yunxiao Shi, Zujie Liang, Xuying Ning, Kai Mei, Kun Wang, Xi Zhu, Min Xu, Yongfeng Zhang

Traditional recommender systems usually take the user-platform paradigm, where users are directly exposed under the control of the platform's recommendation algorithms.

Recommendation Systems

DemonAgent: Dynamically Encrypted Multi-Backdoor Implantation Attack on LLM-based Agent

1 code implementation18 Feb 2025 Pengyu Zhu, Zhenhong Zhou, Yuanhe Zhang, Shilinlu Yan, Kun Wang, Sen Su

As LLM-based agents become increasingly prevalent, backdoors can be implanted into agents through user queries or environment feedback, raising critical concerns regarding safety vulnerabilities.

G-Safeguard: A Topology-Guided Security Lens and Treatment on LLM-based Multi-agent Systems

no code implementations16 Feb 2025 Shilong Wang, Guibin Zhang, Miao Yu, Guancheng Wan, Fanci Meng, Chongye Guo, Kun Wang, Yang Wang

Large Language Model (LLM)-based Multi-agent Systems (MAS) have demonstrated remarkable capabilities in various complex tasks, ranging from collaborative problem-solving to autonomous decision-making.

Decision Making Language Modeling +3

MasRouter: Learning to Route LLMs for Multi-Agent Systems

1 code implementation16 Feb 2025 Yanwei Yue, Guibin Zhang, Boyang Liu, Guancheng Wan, Kun Wang, Dawei Cheng, Yiyan Qi

Multi-agent systems (MAS) powered by Large Language Models (LLMs) have been demonstrated to push the boundaries of LLM capabilities, yet they often incur significant costs and face challenges in dynamic LLM selection.

HumanEval

Machine learning for modelling unstructured grid data in computational physics: a review

no code implementations13 Feb 2025 Sibo Cheng, Marc Bocquet, Weiping Ding, Tobias Sebastian Finn, Rui Fu, Jinlong Fu, Yike Guo, Eleda Johnson, Siyi Li, Che Liu, Eric Newton Moro, Jie Pan, Matthew Piggott, Cesar Quilodran, Prakhar Sharma, Kun Wang, Dunhui Xiao, Xiao Xue, Yong Zeng, Mingrui Zhang, Hao Zhou, Kewei Zhu, Rossella Arcucci

This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics.

Benchmarking

Learning Inverse Laplacian Pyramid for Progressive Depth Completion

no code implementations11 Feb 2025 Kun Wang, Zhiqiang Yan, Junkai Fan, Jun Li, Jian Yang

Depth completion endeavors to reconstruct a dense depth map from sparse depth measurements, leveraging the information provided by a corresponding color image.

Computational Efficiency Depth Completion +2

EvoFlow: Evolving Diverse Agentic Workflows On The Fly

no code implementations11 Feb 2025 Guibin Zhang, Kaijie Chen, Guancheng Wan, Heng Chang, Hong Cheng, Kun Wang, Shuyue Hu, Lei Bai

The past two years have witnessed the evolution of large language model (LLM)-based multi-agent systems from labor-intensive manual design to partial automation (\textit{e. g.}, prompt engineering, communication topology) and eventually to fully automated design.

Large Language Model Prompt Engineering +1

Multi-agent Architecture Search via Agentic Supernet

1 code implementation6 Feb 2025 Guibin Zhang, Luyang Niu, Junfeng Fang, Kun Wang, Lei Bai, Xiang Wang

Large Language Model (LLM)-empowered multi-agent systems extend the cognitive boundaries of individual agents through disciplined collaboration and interaction, while constructing these systems often requires labor-intensive manual designs.

Language Modeling Language Modelling +1

RTLMarker: Protecting LLM-Generated RTL Copyright via a Hardware Watermarking Framework

no code implementations5 Jan 2025 Kun Wang, Kaiyan Chang, Mengdi Wang, Xinqi Zou, Haobo Xu, Yinhe Han, Ying Wang

Recent advances of large language models in the field of Verilog generation have raised several ethical and security concerns, such as code copyright protection and dissemination of malicious code.

Learning-Based Stable Optimal Guidance for Spacecraft Close-Proximity Operations

no code implementations2 Jan 2025 Kun Wang, Roberto Armellin, Adam Evans, Harry Holt, Zheng Chen

This approach ensures that all loss terms related to the control Lyapunov function are either naturally satisfied or replaced by the derived control policy.

LLM-Virus: Evolutionary Jailbreak Attack on Large Language Models

1 code implementation28 Dec 2024 Miao Yu, Junfeng Fang, Yingjie Zhou, Xing Fan, Kun Wang, Shirui Pan, Qingsong Wen

While safety-aligned large language models (LLMs) are increasingly used as the cornerstone for powerful systems such as multi-agent frameworks to solve complex real-world problems, they still suffer from potential adversarial queries, such as jailbreak attacks, which attempt to induce harmful content.

Transfer Learning

Completion as Enhancement: A Degradation-Aware Selective Image Guided Network for Depth Completion

no code implementations26 Dec 2024 Zhiqiang Yan, Zhengxue Wang, Kun Wang, Jun Li, Jian Yang

In this paper, we introduce the Selective Image Guided Network (SigNet), a novel degradation-aware framework that transforms depth completion into depth enhancement for the first time.

Depth Completion Mamba

Depth-Centric Dehazing and Depth-Estimation from Real-World Hazy Driving Video

no code implementations16 Dec 2024 Junkai Fan, Kun Wang, Zhiqiang Yan, Xiang Chen, Shangbing Gao, Jun Li, Jian Yang

In this paper, we study the challenging problem of simultaneously removing haze and estimating depth from real monocular hazy videos.

Depth Estimation

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey

no code implementations3 Dec 2024 Yunkai Dang, Kaichen Huang, Jiahao Huo, Yibo Yan, Sirui Huang, Dongrui Liu, Mengxi Gao, Jie Zhang, Chen Qian, Kun Wang, Yong liu, Jing Shao, Hui Xiong, Xuming Hu

The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV) systems driving advancements in natural language understanding and visual processing, respectively.

Cross-Modal Retrieval Natural Language Understanding +4

SyncVIS: Synchronized Video Instance Segmentation

1 code implementation1 Dec 2024 Rongkun Zheng, Lu Qi, Xi Chen, Yi Wang, Kun Wang, Yu Qiao, Hengshuang Zhao

Recent DETR-based methods have advanced the development of Video Instance Segmentation (VIS) through transformers' efficiency and capability in modeling spatial and temporal information.

Instance Segmentation Segmentation +2

Discovering Latent Structural Causal Models from Spatio-Temporal Data

no code implementations8 Nov 2024 Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yi-An Ma, Rose Yu

Many important phenomena in scientific fields such as climate, neuroscience, and epidemiology are naturally represented as spatiotemporal gridded data with complex interactions.

Causal Discovery Epidemiology +1

NetSafe: Exploring the Topological Safety of Multi-agent Networks

no code implementations21 Oct 2024 Miao Yu, Shilong Wang, Guibin Zhang, Junyuan Mao, Chenlong Yin, Qijiong Liu, Qingsong Wen, Kun Wang, Yang Wang

Large language models (LLMs) have empowered nodes within multi-agent networks with intelligence, showing growing applications in both academia and industry.

Hallucination Misinformation

DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine Domain

1 code implementation19 Oct 2024 Kun Wang, Zhiqiang Yan, Junkai Fan, Wanlu Zhu, Xiang Li, Jun Li, Jian Yang

In this paper, we introduce DCDepth, a novel framework for the long-standing monocular depth estimation task.

Monocular Depth Estimation

On the Role of Attention Heads in Large Language Model Safety

1 code implementation17 Oct 2024 Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li

In light of this, recent research on safety mechanisms has emerged, revealing that when safety representations or component are suppressed, the safety capability of LLMs are compromised.

Attribute Language Modeling +2

PUMA: Empowering Unified MLLM with Multi-granular Visual Generation

1 code implementation17 Oct 2024 Rongyao Fang, Chengqi Duan, Kun Wang, Hao Li, Hao Tian, Xingyu Zeng, Rui Zhao, Jifeng Dai, Hongsheng Li, Xihui Liu

This work represents a significant step towards a truly unified MLLM capable of adapting to the granularity demands of various visual tasks.

Diversity Image Manipulation +1

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning

1 code implementation17 Oct 2024 Guibin Zhang, Haonan Dong, Yuchen Zhang, ZHIXUN LI, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang

Training high-quality deep models necessitates vast amounts of data, resulting in overwhelming computational and memory demands.

Graph Embedding

G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks

no code implementations15 Oct 2024 Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng

Recent advancements in large language model (LLM)-based agents have demonstrated that collective intelligence can significantly surpass the capabilities of individual agents, primarily due to well-crafted inter-agent communication topologies.

HumanEval Language Modelling +2

A Complete Characterization of Learnability for Stochastic Noisy Bandits

no code implementations12 Oct 2024 Steve Hanneke, Kun Wang

With knowledge of $\mathcal{M}$, supposing that the true model $M\in \mathcal{M}$, the objective is to identify an arm $\hat{\pi}$ of near-maximal mean reward $f^M(\hat{\pi})$ with high probability in a bounded number of rounds.

GPR Full-Waveform Inversion through Adaptive Filtering of Model Parameters and Gradients Using CNN

no code implementations11 Oct 2024 Peng Jiang, Kun Wang, Jiaxing Wang, Zeliang Feng, Shengjie Qiao, Runhuai Deng, Fengkai Zhang

GPR full-waveform inversion optimizes the subsurface property model iteratively to match the entire waveform information.

GPR

Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality

1 code implementation7 Oct 2024 Guanyu Zhou, Yibo Yan, Xin Zou, Kun Wang, Aiwei Liu, Xuming Hu

These biases arise from the visual encoder and the Large Language Model (LLM) backbone, affecting the attention mechanism responsible for aligning multimodal inputs.

Causal Inference counterfactual +6

MINER: Mining the Underlying Pattern of Modality-Specific Neurons in Multimodal Large Language Models

1 code implementation7 Oct 2024 Kaichen Huang, Jiahao Huo, Yibo Yan, Kun Wang, Yutao Yue, Xuming Hu

In recent years, multimodal large language models (MLLMs) have significantly advanced, integrating more modalities into diverse applications.

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection

no code implementations6 Oct 2024 Yibo Yan, Shen Wang, Jiahao Huo, Hang Li, Boyan Li, Jiamin Su, Xiong Gao, Yi-Fan Zhang, Tianlong Xu, Zhendong Chu, Aoxiao Zhong, Kun Wang, Hui Xiong, Philip S. Yu, Xuming Hu, Qingsong Wen

As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particularly promising, especially in addressing mathematical reasoning tasks.

Benchmarking Mathematical Reasoning

Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems

no code implementations3 Oct 2024 Guibin Zhang, Yanwei Yue, ZHIXUN LI, Sukwon Yun, Guancheng Wan, Kun Wang, Dawei Cheng, Jeffrey Xu Yu, Tianlong Chen

Recent advancements in large language model (LLM)-powered agents have shown that collective intelligence can significantly outperform individual capabilities, largely attributed to the meticulously designed inter-agent communication topologies.

Language Modelling Large Language Model +1

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models

2 code implementations3 Oct 2024 Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua

To address this, we introduce AlphaEdit, a novel solution that projects perturbation onto the null space of the preserved knowledge before applying it to the parameters.

knowledge editing

Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia

1 code implementation2 Oct 2024 Miao Yu, Junyuan Mao, Guibin Zhang, Jingheng Ye, Junfeng Fang, Aoxiao Zhong, Yang Liu, Yuxuan Liang, Kun Wang, Qingsong Wen

Research into the external behaviors and internal mechanisms of large language models (LLMs) has shown promise in addressing complex tasks in the physical world.

Language Modeling Language Modelling +2

Causal Deciphering and Inpainting in Spatio-Temporal Dynamics via Diffusion Model

no code implementations29 Sep 2024 Yifan Duan, Jian Zhao, Pengcheng, Junyuan Mao, Hao Wu, Jingyu Xu, Shilong Wang, Caoyuan Ma, Kai Wang, Kun Wang, Xuelong Li

To this end, we establish a causal framework for ST predictions, termed CaPaint, which targets to identify causal regions in data and endow model with causal reasoning ability in a two-stage process.

Causal Discovery Image Inpainting

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

1 code implementation25 Sep 2024 Jonathan E. Lee, Min Zhu, Ziqiao Xi, Kun Wang, Yanhua O. Yuan, Lu Lu

In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond the training range has been thoroughly evaluated.

MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI

no code implementations14 Sep 2024 Tobit Klug, Kun Wang, Stefan Ruschke, Reinhard Heckel

In this paper, we propose a deep learning-based test-time-training method for accurate motion estimation.

Motion Estimation

A Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective

no code implementations12 Aug 2024 Chenyu Liu, Xinliang Zhou, Yihao Wu, Yi Ding, Liming Zhai, Kun Wang, Ziyu Jia, Yang Liu

In this paper, we present a comprehensive survey of these studies, delivering a systematic review of graph-related methods in this field from a methodological perspective.

EEG Emotion Recognition

Natural language is not enough: Benchmarking multi-modal generative AI for Verilog generation

1 code implementation11 Jul 2024 Kaiyan Chang, Zhirong Chen, Yunhao Zhou, Wenlong Zhu, Kun Wang, Haobo Xu, Cangyuan Li, Mengdi Wang, Shengwen Liang, Huawei Li, Yinhe Han, Ying Wang

Natural language interfaces have exhibited considerable potential in the automation of Verilog generation derived from high-level specifications through the utilization of large language models, garnering significant attention.

Benchmarking

Backdoor Graph Condensation

1 code implementation3 Jul 2024 Jiahao Wu, Ning Lu, Zeiyu Dai, Kun Wang, Wenqi Fan, Shengcai Liu, Qing Li, Ke Tang

However, while existing graph condensation studies mainly focus on the best trade-off between graph size and the GNNs' performance (model utility), they overlook the security issues of graph condensation.

Backdoor Attack

The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs

1 code implementation18 Jun 2024 Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang

Based on observations, we innovatively introduce the Heterophily Snowflake Hypothesis and provide an effective solution to guide and facilitate research on heterophilic graphs and beyond.

Node Classification

Buffered Asynchronous Secure Aggregation for Cross-Device Federated Learning

no code implementations5 Jun 2024 Kun Wang, Yi-Rui Yang, Wu-Jun Li

Asynchronous federated learning (AFL) is an effective method to address the challenge of device heterogeneity in cross-device federated learning.

Federated Learning

Graph Sparsification via Mixture of Graphs

1 code implementation23 May 2024 Guibin Zhang, Xiangguo Sun, Yanwei Yue, Chonghe Jiang, Kun Wang, Tianlong Chen, Shirui Pan

Specifically, MoG incorporates multiple sparsifier experts, each characterized by unique sparsity levels and pruning criteria, and selects the appropriate experts for each node.

Graph Learning

A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data

1 code implementation23 May 2024 Feng Gu, Jie Lu, Zhen Fang, Kun Wang, Guangquan Zhang

Uncertain changes in data streams present challenges for machine learning models to dynamically adapt and uphold performance in real-time.

Classification Drift Detection

FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering

no code implementations22 May 2024 Yuan Sui, Yufei He, Nian Liu, Xiaoxin He, Kun Wang, Bryan Hooi

A distinctive feature of our approach is its blend of natural language planning with beam search to optimize the selection of reasoning paths.

Common Sense Reasoning Graph Question Answering +6

Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistance

no code implementations CVPR 2024 Junkai Fan, Jiangwei Weng, Kun Wang, Yijun Yang, Jianjun Qian, Jun Li, Jian Yang

Firstly, we introduce a non-aligned reference frame matching module, leveraging an adaptive sliding window to match high-quality reference frames from clear videos.

UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction

2 code implementations25 Mar 2024 Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, Yuxuan Liang

Our UrbanVLP seamlessly integrates multi-granularity information from both macro (satellite) and micro (street-view) levels, overcoming the limitations of prior pretrained models.

Hallucination Text Generation

Tri-Perspective View Decomposition for Geometry-Aware Depth Completion

no code implementations CVPR 2024 Zhiqiang Yan, Yuankai Lin, Kun Wang, Yupeng Zheng, YuFei Wang, Zhenyu Zhang, Jun Li, Jian Yang

Depth completion is a vital task for autonomous driving, as it involves reconstructing the precise 3D geometry of a scene from sparse and noisy depth measurements.

3D geometry Autonomous Driving +1

Spatio-Temporal Fluid Dynamics Modeling via Physical-Awareness and Parameter Diffusion Guidance

no code implementations18 Mar 2024 Hao Wu, Fan Xu, Yifan Duan, Ziwei Niu, Weiyan Wang, Gaofeng Lu, Kun Wang, Yuxuan Liang, Yang Wang

This paper proposes a two-stage framework named ST-PAD for spatio-temporal fluid dynamics modeling in the field of earth sciences, aiming to achieve high-precision simulation and prediction of fluid dynamics through spatio-temporal physics awareness and parameter diffusion guidance.

Quantization

Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework

1 code implementation17 Mar 2024 Kaiyan Chang, Kun Wang, Nan Yang, Ying Wang, Dantong Jin, Wenlong Zhu, Zhirong Chen, Cangyuan Li, Hao Yan, Yunhao Zhou, Zhuoliang Zhao, Yuan Cheng, Yudong Pan, Yiqi Liu, Mengdi Wang, Shengwen Liang, Yinhe Han, Huawei Li, Xiaowei Li

Our 13B model (ChipGPT-FT) has a pass rate improvement compared with GPT-3. 5 in Verilog generation and outperforms in EDA script (i. e., SiliconCompiler) generation with only 200 EDA script data.

All Data Augmentation +1

DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting

no code implementations5 Mar 2024 Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Yuxuan Liang, Yu Zheng, Qingsong Wen, Kun Wang

In this paper, we introduce for the first time the concept of spatio-temporal data dynamic sparse training and are committed to adaptively, dynamically filtering important sensor distributions.

Spatio-Temporal Forecasting

Dueling Over Dessert, Mastering the Art of Repeated Cake Cutting

no code implementations13 Feb 2024 Simina Brânzei, Mohammadtaghi Hajiaghayi, Reed Phillips, Suho Shin, Kun Wang

Alice cuts the cake at a point of her choice, while Bob chooses the left piece or the right piece, leaving the remainder for Alice.

Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching

1 code implementation7 Feb 2024 Tianle Zhang, Yuchen Zhang, Kun Wang, Kai Wang, Beining Yang, Kaipeng Zhang, Wenqi Shao, Ping Liu, Joey Tianyi Zhou, Yang You

Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have raised growing concerns.

Graph Representation Learning

MolTC: Towards Molecular Relational Modeling In Language Models

1 code implementation6 Feb 2024 Junfeng Fang, Shuai Zhang, Chang Wu, Zhengyi Yang, Zhiyuan Liu, Sihang Li, Kun Wang, Wenjie Du, Xiang Wang

Molecular Relational Learning (MRL), aiming to understand interactions between molecular pairs, plays a pivotal role in advancing biochemical research.

Relational Reasoning

Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts

no code implementations6 Feb 2024 Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang, Yuankai Wu, Roger Zimmermann, Yang Wang

In this paper, we address the issue of modeling and estimating changes in the state of the spatio-temporal dynamical systems based on a sequence of observations like video frames.

Optical Flow Estimation

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness

no code implementations2 Feb 2024 Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen

Specifically, GST initially constructs a topology & semantic anchor at a low training cost, followed by performing dynamic sparse training to align the sparse graph with the anchor.

Adversarial Defense Graph Learning

Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model

1 code implementation13 Dec 2023 Hao Wu, Yuxuan Liang, Wei Xiong, Zhengyang Zhou, Wei Huang, Shilong Wang, Kun Wang

Efficiently modeling spatio-temporal (ST) physical processes and observations presents a challenging problem for the deep learning community.

Visual Self-paced Iterative Learning for Unsupervised Temporal Action Localization

1 code implementation12 Dec 2023 Yupeng Hu, Han Jiang, Hao liu, Kun Wang, Haoyu Tang, Liqiang Nie

Recently, temporal action localization (TAL) has garnered significant interest in information retrieval community.

Clustering Incremental Learning +3

TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation

1 code implementation NeurIPS 2023 Rongkun Zheng, Lu Qi, Xi Chen, Yi Wang, Kun Wang, Yu Qiao, Hengshuang Zhao

What we possess are numerous isolated filed-specific datasets, thus, it is appealing to jointly train models across the aggregation of datasets to enhance data volume and diversity.

Instance Segmentation Semantic Segmentation +1

Attend Who is Weak: Enhancing Graph Condensation via Cross-Free Adversarial Training

no code implementations27 Nov 2023 Xinglin Li, Kun Wang, Hanhui Deng, Yuxuan Liang, Di wu

We seminally propose the concept of Shock Absorber (a type of perturbation) that enhances the robustness and stability of the original graphs against changes in an adversarial training fashion.

Node Classification

OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models

1 code implementation11 Oct 2023 Yuhe Liu, Changhua Pei, Longlong Xu, Bohan Chen, Mingze Sun, Zhirui Zhang, Yongqian Sun, Shenglin Zhang, Kun Wang, Haiming Zhang, Jianhui Li, Gaogang Xie, Xidao Wen, Xiaohui Nie, Minghua Ma, Dan Pei

Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of existing information systems.

Hallucination In-Context Learning +2

Causal-Story: Local Causal Attention Utilizing Parameter-Efficient Tuning For Visual Story Synthesis

1 code implementation18 Sep 2023 Tianyi Song, Jiuxin Cao, Kun Wang, Bo Liu, Xiaofeng Zhang

The current state-of-the-art method combines the features of historical captions, historical frames, and the current captions as conditions for generating the current frame.

Image Generation Story Generation

Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception

no code implementations31 Aug 2023 Si Liu, Chen Gao, Yuan Chen, Xingyu Peng, Xianghao Kong, Kun Wang, Runsheng Xu, Wentao Jiang, Hao Xiang, Jiaqi Ma, Miao Wang

Specifically, we analyze the performance changes of different methods under different bandwidths, providing a deep insight into the performance-bandwidth trade-off issue.

Autonomous Driving

The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field

no code implementations19 Aug 2023 Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang, Yang Wang

Despite Graph Neural Networks demonstrating considerable promise in graph representation learning tasks, GNNs predominantly face significant issues with over-fitting and over-smoothing as they go deeper as models of computer vision realm.

Graph Representation Learning

Variable Radiance Field for Real-Life Category-Specifc Reconstruction from Single Image

no code implementations8 Jun 2023 Kun Wang, Zhiqiang Yan, Zhenyu Zhang, Xiang Li, Jun Li, Jian Yang

Our key contributions are: (1) We parameterize the geometry and appearance of the object using a multi-scale global feature extractor, which avoids frequent point-wise feature retrieval and camera dependency.

Contrastive Learning Object +1

Safety Guaranteed Control for Spacecraft Inspection Mission

no code implementations8 Jun 2023 Kun Wang, Tao Meng, Jiakun Lei, Weijia Wang

In order to address this issue, we propose a control strategy based on control barrier functions, summarized as "safety check on kinematics" and "velocity tracking on dynamics" approach.

Adaptive Compatible Performance Control for Spacecraft Attitude Control under Motion Constraints with Guaranteed Accuracy

no code implementations31 May 2023 Jiakun Lei, Tao Meng, Yang Zhu, Kun Wang, Weijia Wang

To tackle this problem, we propose a modified framework called Compatible Performance Control (CPC), which integrates the Prescribed Performance Control (PPC) scheme with a contradiction detection and alleviation strategy.

Composite Triggered Intermittent Control for Constrained Spacecraft Attitude Tracking

no code implementations31 May 2023 Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang, Shujian Sun

Further, the basic intermittent attitude controller is extended to a "constrained version" by introducing a strictly bounded virtual control law and an input saturation compensation auxiliary system.

Philosophy

ConES: Concept Embedding Search for Parameter Efficient Tuning Large Vision Language Models

no code implementations30 May 2023 Huahui Yi, Ziyuan Qin, Wei Xu, Miaotian Guo, Kun Wang, Shaoting Zhang, Kang Li, Qicheng Lao

To achieve this, we propose a Concept Embedding Search (ConES) approach by optimizing prompt embeddings -- without the need of the text encoder -- to capture the 'concept' of the image modality through a variety of task objectives.

Instance Segmentation Prompt Engineering +2

ArtGPT-4: Towards Artistic-understanding Large Vision-Language Models with Enhanced Adapter

1 code implementation12 May 2023 Zhengqing Yuan, Yunhong He, Kun Wang, Yanfang Ye, Lichao Sun

However, a grand challenge of exploiting LLMs for multimodal learning is the size of pre-trained LLMs which are always with billions of parameters.

Image Comprehension Language Modelling

Siamese DETR

1 code implementation CVPR 2023 Zeren Chen, Gengshi Huang, Wei Li, Jianing Teng, Kun Wang, Jing Shao, Chen Change Loy, Lu Sheng

In this work, we present Siamese DETR, a Siamese self-supervised pretraining approach for the Transformer architecture in DETR.

MULTI-VIEW LEARNING Representation Learning

Explore the Power of Synthetic Data on Few-shot Object Detection

no code implementations23 Mar 2023 Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

To construct a representative synthetic training dataset, we maximize the diversity of the selected images via a sample-based and cluster-based method.

Few-Shot Object Detection Object +3

FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning

no code implementations9 Mar 2023 Yi-Rui Yang, Kun Wang, Wu-Jun Li

Based on ConSpar, we further propose a novel FL framework called FedREP, which is Byzantine-robust, communication-efficient and privacy-preserving.

Federated Learning Privacy Preserving

An Effective Crop-Paste Pipeline for Few-shot Object Detection

no code implementations28 Feb 2023 Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

Specifically, we first discover the base images which contain the FP of novel categories and select a certain amount of samples from them for the base and novel categories balance.

Data Augmentation Few-Shot Object Detection +1

Oriented Object Detection in Optical Remote Sensing Images using Deep Learning: A Survey

no code implementations21 Feb 2023 Kun Wang, Zi Wang, Zhang Li, Ang Su, Xichao Teng, Erting Pan, Minhao Liu, Qifeng Yu

Given the rapid development of this field, this paper presents a comprehensive survey of recent advances in oriented object detection.

Object object-detection +3

DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion

no code implementations20 Nov 2022 Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation.

Depth Completion Depth Estimation +2

Event-Triggered Intermittent Prescribed Performance Control for Spacecraft Attitude Reorientation

no code implementations10 Nov 2022 Jiakun Lei, Tao Meng, Kun Wang, Weijia Wang, Zhonghe Jin

The prescribed performance control (PPC) scheme is often employed for the control with guaranteed performance.

R$^2$F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

1 code implementation22 Oct 2022 Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.

Natural Language Inference Retrieval +1

6N-DoF Pose Tracking for Tensegrity Robots

no code implementations29 May 2022 Shiyang Lu, William R. Johnson III, Kun Wang, Xiaonan Huang, Joran Booth, Rebecca Kramer-Bottiglio, Kostas Bekris

To ensure that the pose estimates of rigid elements are physically feasible, i. e., they are not resulting in collisions between rods or with the environment, physical constraints are introduced during the optimization.

Pose Estimation Pose Tracking

Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature

no code implementations8 May 2022 Xueyuan Duan, Yu Fu, Kun Wang

To address the problem that traditional network traffic anomaly detection algorithms do not suffi-ciently mine potential features in long time domain, an anomaly detection method based on mul-ti-scale residual features of network traffic is proposed.

Anomaly Detection Diversity +1

ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification

no code implementations COLING 2022 Meiqi Chen, Yixin Cao, Kunquan Deng, Mukai Li, Kun Wang, Jing Shao, Yan Zhang

In this paper, we propose a novel Event Relational Graph TransfOrmer (ERGO) framework for DECI, which improves existing state-of-the-art (SOTA) methods upon two aspects.

Event Causality Identification Node Classification +2

Few-shot Forgery Detection via Guided Adversarial Interpolation

no code implementations12 Apr 2022 Haonan Qiu, Siyu Chen, Bei Gan, Kun Wang, Huafeng Shi, Jing Shao, Ziwei Liu

Notably, our method is also validated to be robust to choices of majority and minority forgery approaches.

Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion

1 code implementation18 Mar 2022 Zhiqiang Yan, Xiang Li, Kun Wang, Zhenyu Zhang, Jun Li, Jian Yang

To deal with the PDC task, we train a deep network that takes both depth and image as inputs for the dense panoramic depth recovery.

Depth Completion Transfer Learning

Towards Robust 2D Convolution for Reliable Visual Recognition

no code implementations18 Mar 2022 Lida Li, Shuai Li, Kun Wang, Xiangchu Feng, Lei Zhang

2D convolution (Conv2d), which is responsible for extracting features from the input image, is one of the key modules of a convolutional neural network (CNN).

A Recurrent Differentiable Engine for Modeling Tensegrity Robots Trainable with Low-Frequency Data

no code implementations28 Feb 2022 Kun Wang, Mridul Aanjaneya, Kostas Bekris

A model of NASA's icosahedron SUPERballBot on MuJoCo is used as the ground truth system to collect training data.

MuJoCo

Exploring Forensic Dental Identification with Deep Learning

1 code implementation NeurIPS 2021 Yuan Liang, Weikun Han, Liang Qiu, Chen Wu, Yiting shao, Kun Wang, Lei He

In this work, we pioneer to study deep learning for dental forensic identification based on panoramic radiographs.

Deep Learning

INTERN: A New Learning Paradigm Towards General Vision

no code implementations16 Nov 2021 Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao

Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society.

Pitch Preservation In Singing Voice Synthesis

no code implementations11 Oct 2021 Shujun Liu, Hai Zhu, Kun Wang, Huajun Wang

For the phoneme encoder, based on the analysis that same phonemes corresponding to varying pitches can produce similar pronunciations, this encoder is followed by an adversarially trained pitch classifier to enforce the identical phonemes with different pitches mapping into the same phoneme feature space.

Decoder Singing Voice Synthesis

X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph

no code implementations30 Aug 2021 Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He

Different from single object reconstruction from photos, this task has the unique challenge of constructing multiple objects at high resolutions.

3D Reconstruction Anatomy +3

Domain Adaptation for Underwater Image Enhancement

1 code implementation22 Aug 2021 Zhengyong Wang, Liquan Shen, Mei Yu, Kun Wang, Yufei Lin, Mai Xu

However, these methods ignore the significant domain gap between the synthetic and real data (i. e., interdomain gap), and thus the models trained on synthetic data often fail to generalize well to real underwater scenarios.

Domain Adaptation Image Enhancement

FPB: Feature Pyramid Branch for Person Re-Identification

1 code implementation4 Aug 2021 Suofei Zhang, Zirui Yin, Xiofu Wu, Kun Wang, Quan Zhou, Bin Kang

In this paper, we propose a lightweight Feature Pyramid Branch (FPB) to extract features from different layers of networks and aggregate them in a bidirectional pyramid structure.

object-detection Object Detection +1

RigNet: Repetitive Image Guided Network for Depth Completion

no code implementations29 Jul 2021 Zhiqiang Yan, Kun Wang, Xiang Li, Zhenyu Zhang, Jun Li, Jian Yang

However, blurry guidance in the image and unclear structure in the depth still impede the performance of the image guided frameworks.

Depth Completion Depth Estimation +1

Cascading Bandit under Differential Privacy

no code implementations24 May 2021 Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li, Shuo Shao

This paper studies \emph{differential privacy (DP)} and \emph{local differential privacy (LDP)} in cascading bandits.

A mm-Wave Patch Antenna with Broad Bandwidth and a Wide Angular Range

no code implementations17 May 2021 Jonas Kornprobst, Kun Wang, Gerhard Hamberger, Thomas F. Eibert

The wide half power beamwidth is achieved by suitably designed parasitic patches for the first resonant mode.

Conservative Contextual Combinatorial Cascading Bandit

no code implementations17 Apr 2021 Kun Wang, Canzhe Zhao, Shuai Li, Shuo Shao

We propose the novel \emph{conservative contextual combinatorial cascading bandit ($C^4$-bandit)}, a cascading online learning game which incorporates the conservative mechanism.

Decision Making Recommendation Systems

GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set

1 code implementation5 Feb 2021 Hanqing Chao, Kun Wang, Yiwei He, Junping Zhang, Jianfeng Feng

In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.

Gait Recognition

Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation

no code implementations2 Feb 2021 Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He

Second, we can largely boost the robustness of existing ConvNets, proved by: (i) testing on scans with synthetic pathologies, and (ii) training and evaluation on scans of different scanning setups across datasets.

Detecting and quantifying entanglement on near-term quantum devices

1 code implementation28 Dec 2020 Kun Wang, Zhixin Song, Xuanqiang Zhao, Zihe Wang, Xin Wang

Firstly, it decomposes a positive map into a combination of quantum operations implementable on near-term quantum devices.

Quantum Physics Strongly Correlated Electrons

Exploring Instance-Level Uncertainty for Medical Detection

no code implementations23 Dec 2020 Jiawei Yang, Yuan Liang, Yao Zhang, Weinan Song, Kun Wang, Lei He

The ability of deep learning to predict with uncertainty is recognized as key for its adoption in clinical routines.

Lung Nodule Detection

Sim2Sim Evaluation of a Novel Data-Efficient Differentiable Physics Engine for Tensegrity Robots

no code implementations10 Nov 2020 Kun Wang, Mridul Aanjaneya, Kostas Bekris

The results indicate that only 0. 25\% of ground truth data are needed to train a policy that works on the ground truth system when the differentiable engine is used for training against training the policy directly on the ground truth system.

MuJoCo

Spring-Rod System Identification via Differentiable Physics Engine

no code implementations9 Nov 2020 Kun Wang, Mridul Aanjaneya, Kostas Bekris

We propose a novel differentiable physics engine for system identification of complex spring-rod assemblies.

regression

What Have We Achieved on Text Summarization?

1 code implementation EMNLP 2020 Dandan Huang, Leyang Cui, Sen yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang

Deep learning has led to significant improvement in text summarization with various methods investigated and improved ROUGE scores reported over the years.

Text Summarization

Single-Sideband Time-Modulated Phased Array With 2-bit Phased Shifters

no code implementations6 Oct 2020 Yanchang Gao, Gang Ni, Kun Wang, Yiqing Liu, Chong He, Ronghong Jin, Xianling Liang

The timemodulated module is implemented by adding periodic phase modulation to 2-bit phase shifters, which is simpler without performance loss compared to existing SSB time-modulated method.

Accurate Anchor Free Tracking

no code implementations13 Jun 2020 Shengyun Peng, Yunxuan Yu, Kun Wang, Lei He

Specifically, a target object is defined by a bounding box center, tracking offset, and object size.

Object Visual Object Tracking

A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks

no code implementations13 Apr 2020 Kun Wang, WaiChing Sun, Qiang Du

The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification.

Deep Reinforcement Learning reinforcement-learning +1

Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention Networks

2 code implementations13 Apr 2020 Kun Wang, Jun He, Lei Zhang

Recently, several attention mechanisms are proposed to handle the weakly labeled human activity data, which do not require accurate data annotation.

Human Activity Recognition

Oral-3D: Reconstructing the 3D Bone Structure of Oral Cavity from 2D Panoramic X-ray

no code implementations18 Mar 2020 Weinan Song, Yuan Liang, Jiawei Yang, Kun Wang, Lei He

In this paper, we propose a framework, named Oral-3D, to reconstruct the 3D oral cavity from a single PX image and prior information of the dental arch.

3D Reconstruction

Adapting Object Detectors with Conditional Domain Normalization

no code implementations ECCV 2020 Peng Su, Kun Wang, Xingyu Zeng, Shixiang Tang, Dapeng Chen, Di Qiu, Xiaogang Wang

Then this domain-vector is used to encode the features from another domain through a conditional normalization, resulting in different domains' features carrying the same domain attribute.

3D Object Detection Attribute +2

T-Net: Learning Feature Representation with Task-specific Supervision for Biomedical Image Analysis

no code implementations19 Feb 2020 Weinan Song, Yuan Liang, Jiawei Yang, Kun Wang, Lei He

The encoder-decoder network is widely used to learn deep feature representations from pixel-wise annotations in biomedical image analysis.

Decoder Region Proposal +1

Towards the standardization of quantum state verification using optimal strategies

no code implementations3 Feb 2020 Xinhe Jiang, Kun Wang, Kaiyi Qian, Zhaozhong Chen, Zhiyu Chen, Liangliang Lu, Lijun Xia, Fangmin Song, Shining Zhu, Xiaosong Ma

We experimentally obtain the scaling parameter of $r=-0. 88\pm$0. 03 and $-0. 78\pm$0. 07 for nonadaptive and adaptive strategies, respectively.

Quantum Physics Optics

Effective Scaling of Blockchain Beyond Consensus Innovations and Moore's Law

no code implementations7 Jan 2020 Yinqiu Liu, Kai Qian, Jianli Chen, Kun Wang, Lei He

As an emerging technology, blockchain has achieved great success in numerous application scenarios, from intelligent healthcare to smart cities.

Cryptography and Security Distributed, Parallel, and Cluster Computing 68M14 C.2.2

Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference

no code implementations14 May 2019 Yujia Chen, Yang Lou, Kun Wang, Matthew A. Kupinski, Mark A. Anastasio

In this work, a sparsity-driven observer (SDO) that can be employed to optimize hardware by use of a stochastic object model describing object sparsity is described and investigated.

Bayesian Inference Compressive Sensing +1

Time-sync Video Tag Extraction Using Semantic Association Graph

no code implementations3 May 2019 Wenmian Yang, Kun Wang, Na Ruan, Wenyuan Gao, Weijia Jia, Wei Zhao, Nan Liu, Yunyong Zhang

Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF).

TAG

Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors

no code implementations24 Mar 2019 Kun Wang, Jun He, Lei Zhang

Unlike images or videos data which can be easily labeled by human being, sensor data annotation is a time-consuming process.

Human Activity Recognition

A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation

no code implementations8 Mar 2019 Kun Wang, WaiChing Sun, Qiang Du

We introduce a multi-agent meta-modeling game to generate data, knowledge, and models that make predictions on constitutive responses of elasto-plastic materials.

Deep Reinforcement Learning Knowledge Graphs +2

Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning

no code implementations24 Oct 2018 Kun Wang, WaiChing Sun

This paper presents a new meta-modeling framework to employ deep reinforcement learning (DRL) to generate mechanical constitutive models for interfaces.

Deep Reinforcement Learning Game of Go

Ricean K-factor Estimation based on Channel Quality Indicator in OFDM Systems using Neural Network

no code implementations15 Aug 2018 Kun Wang

Ricean channel model is widely used in wireless communications to characterize the channels with a line-of-sight path.

General Classification

Scene Graph Generation from Objects, Phrases and Region Captions

1 code implementation ICCV 2017 Yikang Li, Wanli Ouyang, Bolei Zhou, Kun Wang, Xiaogang Wang

Object detection, scene graph generation and region captioning, which are three scene understanding tasks at different semantic levels, are tied together: scene graphs are generated on top of objects detected in an image with their pairwise relationship predicted, while region captioning gives a language description of the objects, their attributes, relations, and other context information.

Graph Generation object-detection +3

Crafting GBD-Net for Object Detection

1 code implementation8 Oct 2016 Xingyu Zeng, Wanli Ouyang, Junjie Yan, Hongsheng Li, Tong Xiao, Kun Wang, Yu Liu, Yucong Zhou, Bin Yang, Zhe Wang, Hui Zhou, Xiaogang Wang

The effectiveness of GBD-Net is shown through experiments on three object detection datasets, ImageNet, Pascal VOC2007 and Microsoft COCO.

Object object-detection +1

Cannot find the paper you are looking for? You can Submit a new open access paper.