no code implementations • ECCV 2020 • Shuo Wang, Yuexiang Li, Kai Ma, Ruhui Ma, Haibing Guan, Yefeng Zheng
In this paper, we investigate the overlapping problem of recent uncertainty-based approaches and propose to alleviate the issue by taking representativeness into consideration.
no code implementations • ECCV 2020 • Shuo Wang, Jun Yue, Jianzhuang Liu, Qi Tian, Meng Wang
It is a challenging problem since (1) the identifying process is susceptible to over-fitting with limited samples of an object, and (2) the sample imbalance between a base (known knowledge) category and a novel category is easy to bias the recognition results.
no code implementations • ECCV 2020 • Xiaobo Wang, Tianyu Fu, Shengcai Liao, Shuo Wang, Zhen Lei, Tao Mei
Knowledge distillation is an effective tool to compress large pre-trained Convolutional Neural Networks (CNNs) or their ensembles into models applicable to mobile and embedded devices.
no code implementations • 17 Jun 2025 • Hexian Ni, Tao Lu, Haoyuan Hu, Yinghao Cai, Shuo Wang
In this paper, we present a novel efficient query selection and preference-guided exploration method, called SENIOR, which could select the meaningful and easy-to-comparison behavior segment pairs to improve human feedback-efficiency and accelerate policy learning with the designed preference-guided intrinsic rewards.
no code implementations • 14 Jun 2025 • Haoyu Zhai, Shuo Wang, Pirouz Naghavi, Qingying Hao, Gang Wang
The key intuition is to leverage a generative model's memorization effect and approximate the inverse function of Gaussian blur for face restoration.
1 code implementation • 12 Jun 2025 • Zhensheng Jin, Xinze Li, Yifan Ji, Chunyi Peng, Zhenghao Liu, Qi Shi, Yukun Yan, Shuo Wang, Furong Peng, Ge Yu
Recent advances in Chain-of-Thought (CoT) prompting have substantially improved the reasoning capabilities of Large Language Models (LLMs).
no code implementations • 12 Jun 2025 • Shuo Wang, Jihao Zhang
Segment importance, location, and center-ness are predicted, followed by key shot selection using Non-Maximum Suppression (NMS) and the Kernel Temporal Segmentation (KTS) algorithm.
1 code implementation • 11 Jun 2025 • Changxin Ke, Rui Zhang, Shuo Wang, Li Ding, Guangli Li, Yuanbo Wen, Shuoming Zhang, Ruiyuan Xu, Jin Qin, Jiaming Guo, Chenxi Wang, Ling Li, Qi Guo, Yunji Chen
MSL consists of two models, a Translator and a Tester.
1 code implementation • 9 Jun 2025 • MiniCPM Team, Chaojun Xiao, YuXuan Li, Xu Han, Yuzhuo Bai, Jie Cai, Haotian Chen, Wentong Chen, Xin Cong, Ganqu Cui, Ning Ding, Shengdan Fan, Yewei Fang, Zixuan Fu, Wenyu Guan, Yitong Guan, Junshao Guo, Yufeng Han, Bingxiang He, Yuxiang Huang, Cunliang Kong, Qiuzuo Li, Siyuan Li, Wenhao Li, Yanghao Li, Yishan Li, Zhen Li, Dan Liu, Biyuan Lin, Yankai Lin, Xiang Long, Quanyu Lu, Yaxi Lu, Peiyan Luo, Hongya Lyu, Litu Ou, Yinxu Pan, Zekai Qu, Qundong Shi, Zijun Song, Jiayuan Su, Zhou Su, Ao Sun, Xianghui Sun, Peijun Tang, Fangzheng Wang, Feng Wang, Shuo Wang, Yudong Wang, Yesai Wu, Zhenyu Xiao, Jie Xie, Zihao Xie, Yukun Yan, Jiarui Yuan, Kaihuo Zhang, Lei Zhang, Linyue Zhang, Xueren Zhang, Yudi Zhang, Hengyu Zhao, Weilin Zhao, Weilun Zhao, Yuanqian Zhao, Zhi Zheng, Ge Zhou, Jie zhou, Wei Zhou, Zihan Zhou, Zixuan Zhou, Zhiyuan Liu, Guoyang Zeng, Chao Jia, Dahai Li, Maosong Sun
Specifically, in terms of model architecture, we propose InfLLM v2, a trainable sparse attention mechanism that accelerates both prefilling and decoding phases for long-context processing.
no code implementations • 6 Jun 2025 • Kaiyuan Chen, Yuhan Suo, Shaowei Cui, Yuanqing Xia, Wannian Liang, Shuo Wang
This paper addresses the problem of trajectory optimization for unmanned aerial vehicles (UAVs) performing time-sensitive medical deliveries in urban environments.
1 code implementation • 30 May 2025 • Xiaoang Xu, Shuo Wang, Xu Han, Zhenghao Liu, Huijia Wu, Peipei Li, Zhiyuan Liu, Maosong Sun, Zhaofeng He
Specifically, A*-Thought can improve the performance of QwQ-32B by 2. 39$\times$ with low-budget and reduce the length of the output token by nearly 50% with high-budget.
1 code implementation • 27 May 2025 • Xuanle Zhao, Zilin Sang, YuXuan Li, Qi Shi, Weilun Zhao, Shuo Wang, Duzhen Zhang, Xu Han, Zhiyuan Liu, Maosong Sun
Building on this idea, we propose AutoReproduce, a multi-agent framework capable of automatically reproducing experiments described in research papers in an end-to-end manner.
2 code implementations • 26 May 2025 • Shuo Wang, Yun Cheng, Qingye Meng, Olga Saukh, Jiang Zhang, Jingfang Fan, YuanTing Zhang, Xingyuan Yuan, Lothar Thiele
Air quality forecasting (AQF) is critical for public health and environmental management, yet remains challenging due to the complex interplay of emissions, meteorology, and chemical transformations.
no code implementations • 26 May 2025 • Xiaorong Wang, Ting Yang, Zhu Zhang, Shuo Wang, Zihan Zhou, Liner Yang, Zhiyuan Liu, Maosong Sun
Moreover, we introduce a hybrid in-context learning approach that leverages human annotations to enhance the performance of both local and global evaluations.
2 code implementations • 24 May 2025 • Xuanhe Zhou, Junxuan He, Wei Zhou, Haodong Chen, Zirui Tang, Haoyu Zhao, Xin Tong, Guoliang Li, Youmin Chen, Jun Zhou, Zhaojun Sun, Binyuan Hui, Shuo Wang, Conghui He, Zhiyuan Liu, Jingren Zhou, Fan Wu
The integration of large language model (LLM) and data management (DATA) is rapidly redefining both domains.
no code implementations • 22 May 2025 • Zeyu Wei, Shuo Wang, Xiaohui Rong, Xuemin Liu, He Li
Hallucinations -- plausible yet erroneous outputs -- remain a critical barrier to reliable deployment of large language models (LLMs).
no code implementations • 20 May 2025 • Yingli Shen, Wen Lai, Shuo Wang, Kangyang Luo, Alexander Fraser, Maosong Sun
Continued pretraining and instruction tuning on large-scale multilingual data have proven to be effective in scaling large language models (LLMs) to low-resource languages.
1 code implementation • 19 May 2025 • Zekai Li, Xinhao Zhong, Samir Khaki, Zhiyuan Liang, Yuhao Zhou, Mingjia Shi, Ziqiao Wang, Xuanlei Zhao, Wangbo Zhao, Ziheng Qin, Mengxuan Wu, Pengfei Zhou, Haonan Wang, David Junhao Zhang, Jia-Wei Liu, Shaobo Wang, Dai Liu, Linfeng Zhang, Guang Li, Kun Wang, Zheng Zhu, Zhiheng Ma, Joey Tianyi Zhou, Jiancheng Lv, Yaochu Jin, Peihao Wang, Kaipeng Zhang, Lingjuan Lyu, Yiran Huang, Zeynep Akata, Zhiwei Deng, Xindi Wu, George Cazenavette, Yuzhang Shang, Justin Cui, Jindong Gu, Qian Zheng, Hao Ye, Shuo Wang, Xiaobo Wang, Yan Yan, Angela Yao, Mike Zheng Shou, Tianlong Chen, Hakan Bilen, Baharan Mirzasoleiman, Manolis Kellis, Konstantinos N. Plataniotis, Zhangyang Wang, Bo Zhao, Yang You, Kai Wang
In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance comparable to those trained on the original datasets.
no code implementations • 16 May 2025 • Shuo Wang, Tong Ren, Nan Cheng, Rong Wang, Li Zhang
We developed cardiac output analysis and virtual angiography systems, implemented guidewire 3D reconstruction using binocular stereo vision, and evaluated the system through angiography validation and CABG training applications.
no code implementations • 14 May 2025 • Yili He, Yan Zhu, Peiyao Fu, Ruijie Yang, Tianyi Chen, Zhihua Wang, QuanLin Li, Pinghong Zhou, Xian Yang, Shuo Wang
Pre-training on image-text colonoscopy records offers substantial potential for improving endoscopic image analysis, but faces challenges including non-informative background images, complex medical terminology, and ambiguous multi-lesion descriptions.
1 code implementation • 6 May 2025 • Hao Liao, Wensheng Lu, Jianxun Lian, Mingqi Wu, Shuo Wang, Yong Zhang, Yitian Huang, Mingyang Zhou, Xing Xie
Large Language Models (LLMs) have shown promise for generative recommender systems due to their transformative capabilities in user interaction.
no code implementations • 28 Apr 2025 • Shuo Wang, Tong Ren, Nan Cheng, Li Zhang, Rong Wang
Objective: To develop and evaluate a dynamic cardiovascular holographic visualization tool for preoperative CABG planning.
no code implementations • 25 Apr 2025 • Hanrui Wang, Shuo Wang, Chun-Shien Lu, Isao Echizen
It surpasses state-of-the-art attacks by 15. 5% and 9. 82% in success rate on standard and privacy-preserving face recognition systems, respectively.
1 code implementation • 12 Apr 2025 • Feng Lv, Chunlong Xia, Shuo Wang, Huo Cao
Building on RT-DETR as our base detector, we first introduce a local object-level feature alignment module to significantly enhance the feature representation of domain invariance during object transfer.
1 code implementation • 8 Apr 2025 • Haoyu Wang, Yujia Fu, Zhu Zhang, Shuo Wang, Zirui Ren, Xiaorong Wang, Zhili Li, Chaoqun He, Bo An, Zhiyuan Liu, Maosong Sun
Long-form generation is crucial for a wide range of practical applications, typically categorized into short-to-long and long-to-long generation.
no code implementations • 3 Apr 2025 • Zidong Yu, Shuo Wang, Nan Jiang, Weiqiang Huang, Xu Han, Junliang Du
Harmful text detection has become a crucial task in the development and deployment of large language models, especially as AI-generated content continues to expand across digital platforms.
no code implementations • 1 Apr 2025 • Chenguang Xiao, Abhirup Ghosh, Han Wu, Shuo Wang, Diederick van Thiel
Machine unlearning, which enables a model to forget specific data upon request, is increasingly relevant in the era of privacy-centric machine learning, particularly within federated learning (FL) environments.
1 code implementation • 28 Mar 2025 • Zhiyu Yang, Shuo Wang, Yukun Yan, Yang Deng
To address this gap, we introduce DSDBench: the Data Science Debugging Benchmark, the first benchmark for systematic evaluation of LLMs on multi-hop error tracing and multi-bug detection in data science code debugging.
1 code implementation • CVPR 2025 • Zhiwei Yang, Yucong Meng, Kexue Fu, Feilong Tang, Shuo Wang, Zhijian Song
To mine fine-grained knowledge from visual features, our VC module first proposes Static Visual Calibration (SVC) to propagate fine-grained knowledge in a non-parametric manner.
1 code implementation • 13 Mar 2025 • Fengxiang Wang, Hongzhen Wang, Yulin Wang, Di Wang, Mingshuo Chen, Haiyan Zhao, Yangang Sun, Shuo Wang, Long Lan, Wenjing Yang, Jing Zhang
Recent advances in self-supervised learning for Vision Transformers (ViTs) have fueled breakthroughs in remote sensing (RS) foundation models.
no code implementations • 11 Mar 2025 • Peng Hao, Chaofan Zhang, Dingzhe Li, Xiaoge Cao, Xiaoshuai Hao, Shaowei Cui, Shuo Wang
Significant progress has been made in vision-language models.
no code implementations • 6 Mar 2025 • Yansong Gao, Huaibing Peng, Hua Ma, Zhiyang Dai, Shuo Wang, Hongsheng Hu, Anmin Fu, Minhui Xue
Recognizing the distinct nature of loss between adversarial and clean examples, we exploit this temporal imprint for AE detection by proposing TRAIT (TRaceable Adversarial temporal trajectory ImprinTs).
no code implementations • 5 Mar 2025 • Qingyu Fan, Yinghao Cai, Chao Li, Wenzhe He, Xudong Zheng, Tao Lu, Bin Liang, Shuo Wang
Robotic grasping in scenes with transparent and specular objects presents great challenges for methods relying on accurate depth information.
1 code implementation • 5 Mar 2025 • Fanwen Wang, Zi Wang, Yan Li, Jun Lyu, Chen Qin, Shuo Wang, Kunyuan Guo, Mengting Sun, Mingkai Huang, Haoyu Zhang, Michael Tänzer, Qirong Li, Xinran Chen, Jiahao Huang, Yinzhe Wu, Kian Anvari Hamedani, Yuntong Lyu, Longyu Sun, Qing Li, Ziqiang Xu, Bingyu Xin, Dimitris N. Metaxas, Narges Razizadeh, Shahabedin Nabavi, George Yiasemis, Jonas Teuwen, Zhenxi Zhang, Sha Wang, Chi Zhang, Daniel B. Ennis, Zhihao Xue, Chenxi Hu, Ruru Xu, Ilkay Oksuz, Donghang Lyu, Yanxin Huang, Xinrui Guo, Ruqian Hao, Jaykumar H. Patel, Guanke Cai, Binghua Chen, Yajing Zhang, Sha Hua, Zhensen Chen, Qi Dou, Xiahai Zhuang, Qian Tao, Wenjia Bai, Jing Qin, He Wang, Claudia Prieto, Michael Markl, Alistair Young, Hao Li, Xihong Hu, Lianmin Wu, Xiaobo Qu, Guang Yang, Chengyan Wang
In addition, through a detailed analysis of the results submitted to the challenge, we have also made several findings, including: 1) adaptive prompt-learning embedding is an effective means for achieving strong generalization in reconstruction models; 2) enhanced data consistency based on physics-informed networks is also an effective pathway toward a universal model; 3) traditional evaluation metrics have limitations when assessing ground-truth references with moderate or lower image quality, highlighting the need for subjective evaluation methods.
1 code implementation • 4 Mar 2025 • Shuo Wang, Tong Ren, Nan Cheng, Rong Wang, Li Zhang
Purpose: This study proposes a novel anatomically-driven dynamic modeling framework for coronary arteries using skeletal skinning weights computation, aiming to achieve precise control over vessel deformation while maintaining real-time performance for surgical simulation applications.
no code implementations • 25 Feb 2025 • JIA YU, Yan Zhu, Peiyao Fu, Tianyi Chen, Junbo Huang, QuanLin Li, Pinghong Zhou, Zhihua Wang, Fei Wu, Shuo Wang, Xian Yang
Diffusion models have emerged as a promising solution for generating synthetic polyp images, but the image generation process in current models mainly relies on segmentation masks as the condition, limiting their ability to capture the full clinical context.
no code implementations • 18 Feb 2025 • Shuo Wang, Renhao Li, Xi Chen, Yulin Yuan, Derek F. Wong, Min Yang
The findings demonstrate the sensitivity of all three models to HEXACO personality traits and, more importantly, a consistent variation in the biases, negative sentiment and toxicity of their output.
no code implementations • 18 Feb 2025 • Sifan Zhou, Shuo Wang, Zhihang Yuan, Mingjia Shi, Yuzhang Shang, Dawei Yang
Large Language Models (LLMs) fine-tuning technologies have achieved remarkable results.
1 code implementation • 17 Feb 2025 • Zhe Huang, Shuo Wang, Yongcai Wang, Lei Wang
Experimental study on both simulated and real-world datasets demonstrates that the proposed framework CoDiff consistently outperforms existing relevant methods in terms of the collaborative object detection performance, and exhibits highly desired robustness when the pose and delay information of agents is with high-level noise.
1 code implementation • 17 Feb 2025 • Yingli Shen, Wen Lai, Shuo Wang, Xueren Zhang, Kangyang Luo, Alexander Fraser, Maosong Sun
The rapid development of multilingual large language models (LLMs) highlights the need for high-quality, diverse, and clean multilingual datasets.
no code implementations • 13 Feb 2025 • Shuo Wang, Keke Gai, Jing Yu, Liehuang Zhu, Qi Wu
Vertical Federated Learning (VFL) has garnered significant attention as a privacy-preserving machine learning framework for sample-aligned feature federation.
no code implementations • 11 Feb 2025 • Fujiao Ju, Yuxuan Wang, Shuo Wang, Chengyin Wang, Yinbo Chen, Jianfeng Li, Mingjie Dong, Bin Fang, Qianyu Zhuang
Next, we align the real spine model reconstructed from CT images with the standard skeletal model.
1 code implementation • 4 Feb 2025 • Jinda Lu, Junkang Wu, Jinghan Li, Xiaojun Jia, Shuo Wang, Yifan Zhang, Junfeng Fang, Xiang Wang, Xiangnan He
Direct Preference Optimization (DPO) has shown effectiveness in aligning multi-modal large language models (MLLM) with human preferences.
1 code implementation • 4 Feb 2025 • Bowen Ping, Jiali Zeng, Fandong Meng, Shuo Wang, Jie zhou, Shanghang Zhang
Finally, we apply step-level DPO using the collected stepwise preference pairs.
no code implementations • 4 Feb 2025 • Shuo Wang, Bokui Wang, Zhixiang Shen, Boyan Deng, Zhao Kang
To address these issues, we propose the Multi-Domain Graph Foundation Model (MDGFM), a unified framework that aligns and leverages cross-domain topological information to facilitate robust knowledge transfer.
5 code implementations • 3 Feb 2025 • Ganqu Cui, Lifan Yuan, Zefan Wang, Hanbin Wang, Wendi Li, Bingxiang He, Yuchen Fan, Tianyu Yu, Qixin Xu, Weize Chen, Jiarui Yuan, Huayu Chen, Kaiyan Zhang, Xingtai Lv, Shuo Wang, Yuan YAO, Xu Han, Hao Peng, Yu Cheng, Zhiyuan Liu, Maosong Sun, BoWen Zhou, Ning Ding
While dense rewards also offer an appealing choice for the reinforcement learning (RL) of LLMs since their fine-grained rewards have the potential to address some inherent issues of outcome rewards, such as training efficiency and credit assignment, this potential remains largely unrealized.
no code implementations • 1 Feb 2025 • Jiangyong Yu, Sifan Zhou, Dawei Yang, Shuo Wang, Shuoyu Li, Xing Hu, Chen Xu, Zukang Xu, Changyong Shu, Zhihang Yuan
In this paper, we propose MQuant, a post-training quantization (PTQ) framework designed to tackle the unique challenges of multimodal large language models (MLLMs).
no code implementations • 31 Jan 2025 • Junxiang Qiu, Shuo Wang, Jinda Lu, Lin Liu, Houcheng Jiang, Yanbin Hao
Existing caching methods accelerate generation by reusing DiT features from the previous time step and skipping calculations in the next, but they tend to locate and cache low-error modules without focusing on reducing caching-induced errors, resulting in a sharp decline in generated content quality when increasing caching intensity.
1 code implementation • 11 Jan 2025 • Xuanle Zhao, Xianzhen Luo, Qi Shi, Chi Chen, Shuo Wang, Wanxiang Che, Zhiyuan Liu, Maosong Sun
: (1) Low executability and poor restoration of chart details in the generated code and (2) Lack of large-scale and diverse training data.
no code implementations • 9 Jan 2025 • Shoucheng Song, Youfang Lin, Sheng Han, Chang Yao, Hao Wu, Shuo Wang, Kai Lv
This paper first defines two communication delay settings in MARL and emphasizes their harm to collaboration.
no code implementations • CVPR 2025 • Shixin Li, Chaoxiang He, Xiaojing Ma, Bin Benjamin Zhu, Shuo Wang, Hongsheng Hu, Dongmei Zhang, Linchen Yu
Adversarial attacks threaten the integrity of deep neural networks (DNNs), particularly in high-stakes applications.
no code implementations • CVPR 2025 • Shuo Wang, Wanting Li, Yongcai Wang, Zhaoxin Fan, Zhe Huang, Xudong Cai, Jian Zhao, Deying Li
To address this challenge, this paper proposes MambaVO, which conducts robust initialization, Mamba-based sequential matching refinement, and smoothed training to enhance the matching quality and improve the pose estimation in deep visual odometry.
no code implementations • 27 Dec 2024 • Shuo Wang, Chihang Wang, Jia Gao, Zhen Qi, Hongye Zheng, Xiaoxuan Liao
This study proposes a knowledge distillation algorithm based on large language models and feature alignment, aiming to effectively transfer the knowledge of large pre-trained models into lightweight student models, thereby reducing computational costs while maintaining high model performance.
no code implementations • 27 Dec 2024 • Xudong Cai, Yongcai Wang, Zhaoxin Fan, Deng Haoran, Shuo Wang, Wanting Li, Deying Li, Lun Luo, Minhang Wang, Jintao Xu
To refine the 3D model at novel viewpoints, we propose a Confidence Aware Depth Alignment (CADA) module to refine the coarse depth maps by aligning their confident parts with estimated depths by a Mono-depth model.
no code implementations • 22 Dec 2024 • Xu Wang, Shengeng Tang, Peipei Song, Shuo Wang, Dan Guo, Richang Hong
Sign Language Production (SLP) aims to generate sign videos corresponding to spoken language sentences, where the conversion of sign Glosses to Poses (G2P) is the key step.
no code implementations • 21 Dec 2024 • Chenguang Xiao, Zheming Zuo, Shuo Wang
Federated learning (FL) triggers intra-client and inter-client class imbalance, with the latter compared to the former leading to biased client updates and thus deteriorating the distributed models.
no code implementations • 16 Dec 2024 • Shuo Wang, Issei Sato
In-context learning (ICL) enables large language models (LLMs) to adapt to new tasks without fine-tuning by leveraging contextual information provided within a prompt.
1 code implementation • 15 Dec 2024 • Zhiwei Yang, Yucong Meng, Kexue Fu, Shuo Wang, Zhijian Song
To this end, we first view the attention as a novel directed graph and propose the Graph Category Representation module to implicitly regularize the interaction among class-patch entities.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
1 code implementation • 14 Dec 2024 • Yuan Tian, Shuo Wang, Guangtao Zhai
Face de-identification (DeID) has been widely studied for common scenes, but remains under-researched for medical scenes, mostly due to the lack of large-scale patient face datasets.
no code implementations • 11 Dec 2024 • Shuo Wang, Kuojun Yang, Zelin Ji, Qinchuan Zhang, Huiqing Pan
However, current automatic identification methods require the input of key parameters such as the carrier frequency, which is necessary to convert the radio frequency (RF) to a base-band signal before it can be used for identification.
no code implementations • 9 Dec 2024 • Zhen Qi, Jiajing Chen, Shuo Wang, Bingying Liu, Hongye Zheng, Chihang Wang
This study aims to explore the performance improvement method of large language models based on GPT-4 under the multi-task learning framework and conducts experiments on two tasks: text classification and automatic summary generation.
no code implementations • 9 Dec 2024 • Yu Zhong, Rui Zhang, Zihao Zhang, Shuo Wang, Chuan Fang, Xishan Zhang, Jiaming Guo, Shaohui Peng, Di Huang, Yanyang Yan, Xing Hu, Ping Tan, Qi Guo
Vision-and-Language Navigation (VLN) is a challenging task that requires an agent to navigate through photorealistic environments following natural-language instructions.
no code implementations • 29 Nov 2024 • Chenguang Xiao, Shuo Wang
However, we spot a problem in the traditional cumulation of the momentum which is suboptimal in the Federated Learning systems.
1 code implementation • 22 Nov 2024 • Zheni Zeng, Yuxuan Chen, Shi Yu, Ruobing Wang, Yukun Yan, Zhenghao Liu, Shuo Wang, Xu Han, Zhiyuan Liu, Maosong Sun
Although retrieval-augmented generation (RAG) remains essential for knowledge-based question answering (KBQA), current paradigms face critical challenges under specific domains.
no code implementations • 19 Nov 2024 • Jiajing Chen, Shuo Wang, Zhen Qi, Zhenhong Zhang, Chihang Wang, Hongye Zheng
This research introduces a novel text generation model that combines BERT's semantic interpretation strengths with GPT-4's generative capabilities, establishing a high standard in generating coherent, contextually accurate language.
no code implementations • 13 Nov 2024 • Zelin Ji, Shuo Wang, Kuojun Yang, Qinchuan Zhang, Peng Ye
The numerical results show that the proposed noise reduction network achieves an accuracy improvement of over 20\% in low SNR scenarios, and the TNR-AMC framework can improve the classification accuracy under unstable SNRs.
no code implementations • 6 Nov 2024 • Yuxin Dong, Shuo Wang, Hongye Zheng, Jiajing Chen, Zhenhong Zhang, Chihang Wang
This study proposes a scheme to process graph structure data by combining graph neural network (GNN), so that the model can capture the complex relationship between entities, thereby improving the knowledge consistency and reasoning ability of the generated text.
no code implementations • 30 Oct 2024 • Xujia Wang, Haiyan Zhao, Shuo Wang, Hanqing Wang, Zhiyuan Liu
Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA have significantly improved the adaptation of LLMs to downstream tasks in a resource-efficient manner.
no code implementations • 25 Oct 2024 • Xingyu Zhu, Beier Zhu, Yi Tan, Shuo Wang, Yanbin Hao, Hanwang Zhang
Vision-language models, such as CLIP, have shown impressive generalization capacities when using appropriate text descriptions.
1 code implementation • 21 Oct 2024 • Xinze Li, Hanbin Wang, Zhenghao Liu, Shi Yu, Shuo Wang, Yukun Yan, Yukai Fu, Yu Gu, Ge Yu
Specifically, it consists of a code structure aware retriever (CONAN-R) and a dual-view code representation-based retrieval-augmented generation model (CONAN-G).
no code implementations • 18 Oct 2024 • Chihang Wang, Yuxin Dong, Zhenhong Zhang, Ruotong Wang, Shuo Wang, Jiajing Chen
This paper focuses on the development of an advanced intelligent article scoring system that not only assesses the overall quality of written work but also offers detailed feature-based scoring tailored to various article genres.
1 code implementation • 18 Oct 2024 • Runchu Tian, Yanghao Li, Yuepeng Fu, Siyang Deng, Qinyu Luo, Cheng Qian, Shuo Wang, Xin Cong, Zhong Zhang, Yesai Wu, Yankai Lin, Huadong Wang, Xiaojiang Liu
These experiments reveal that while most current models are robust against the "lost in the middle" issue, there exist significant biases related to the spacing of relevant information pieces.
1 code implementation • 17 Oct 2024 • Xinze Li, Sen Mei, Zhenghao Liu, Yukun Yan, Shuo Wang, Shi Yu, Zheni Zeng, Hao Chen, Ge Yu, Zhiyuan Liu, Maosong Sun, Chenyan Xiong
Our experiments on various knowledge-intensive tasks demonstrate that DDR significantly outperforms the SFT method, particularly for LLMs with smaller-scale parameters that depend more on the retrieved knowledge.
1 code implementation • 14 Oct 2024 • Shi Yu, Chaoyue Tang, Bokai Xu, Junbo Cui, Junhao Ran, Yukun Yan, Zhenghao Liu, Shuo Wang, Xu Han, Zhiyuan Liu, Maosong Sun
In this pipeline, instead of first parsing the document to obtain text, the document is directly embedded using a VLM as an image and then retrieved to enhance the generation of a VLM.
1 code implementation • 12 Oct 2024 • Zihan Zhou, Chong Li, Xinyi Chen, Shuo Wang, Yu Chao, Zhili Li, Haoyu Wang, Rongqiao An, Qi Shi, Zhixing Tan, Xu Han, Xiaodong Shi, Zhiyuan Liu, Maosong Sun
The proposed LLM$\times$MapReduce framework splits the entire document into several chunks for LLMs to read and then aggregates the intermediate answers to produce the final output.
1 code implementation • 11 Oct 2024 • Ruobing Wang, Daren Zha, Shi Yu, Qingfei Zhao, Yuxuan Chen, YiXuan Wang, Shuo Wang, Yukun Yan, Zhenghao Liu, Xu Han, Zhiyuan Liu, Maosong Sun
Retrieval-Augmented Generation (RAG) mitigates issues of the factual errors and hallucinated outputs generated by Large Language Models (LLMs) in open-domain question-answering tasks (OpenQA) via introducing external knowledge.
1 code implementation • 29 Sep 2024 • Kexue Fu, Xiaoyuan Luo, Linhao Qu, Shuo Wang, Ying Xiong, Ilias Maglogiannis, Longxiang Gao, Manning Wang
Unlike few-shot learning methods in natural images that can leverage the labels of each image, existing few-shot WSI classification methods only utilize a small number of fine-grained labels or weakly supervised slide labels for training in order to avoid expensive fine-grained annotation.
1 code implementation • 27 Sep 2024 • Shuo Wang, Binbin Huang, Ruoyu Wang, Shenghua Gao
To tackle the dynamic contents and the occlusions in complex scenes, we present a space-time 2D Gaussian Splatting approach.
1 code implementation • 26 Sep 2024 • Yuxin Jia, Youfang Lin, Jing Yu, Shuo Wang, Tianhao Liu, Huaiyu Wan
The other branch employs patches to capture short-term information and aggregate the global representation of the series.
1 code implementation • 25 Sep 2024 • Zhixiang Shen, Shuo Wang, Zhao Kang
Moreover, existing methods primarily rely on contrastive learning to maximize mutual information across different graphs, limiting them to multiplex graph redundant scenarios and failing to capture view-unique task-relevant information.
1 code implementation • 23 Sep 2024 • Ahjol Senbi, Tianyu Huang, Fei Lyu, Qing Li, Yuhui Tao, Wei Shao, Qiang Chen, Chengyan Wang, Shuo Wang, Tao Zhou, Yizhe Zhang
We name this model EvanySeg (Evaluation of Any Segmentation in Medical Images).
1 code implementation • 20 Sep 2024 • Mengyun Qiao, Kathryn A McGurk, Shuo Wang, Paul M. Matthews, Declan P O Regan, Wenjia Bai
To this end, we developed a novel conditional generative model, MeshHeart, to learn the distribution of cardiac shape and motion patterns.
no code implementations • 18 Sep 2024 • Zhihui He, Chengyuan Wang, Shidong Yang, Li Chen, Yanheng Zhou, Shuo Wang
Therefore, we propose DTAN, a differentiable collision-supervised tooth arrangement network, decoupling predicting tasks and feature modeling.
no code implementations • 18 Sep 2024 • Wang Xu, Shuo Wang, Weilin Zhao, Xu Han, Yukun Yan, Yudi Zhang, Zhe Tao, Zhiyuan Liu, Wanxiang Che
To address this limitation, researchers have proposed duplex models.
1 code implementation • 13 Sep 2024 • Shuo Wang, Chunlong Xia, Feng Lv, Yifeng Shi
However, compared to dense supervision detectors like the YOLO series, the Hungarian matching provides much sparser supervision, leading to insufficient model training and difficult to achieve optimal results.
no code implementations • 12 Sep 2024 • Hanqiu Wang, Zihao Zhan, Haoqi Shan, Siqi Dai, Max Panoff, Shuo Wang
The advent and growing popularity of Virtual Reality (VR) and Mixed Reality (MR) solutions have revolutionized the way we interact with digital platforms.
no code implementations • 11 Sep 2024 • Limeng Wang, Shuo Wang, Na Wang, Yuze Ma, Yang Li
In order to improve energy utilization and reduce carbon emissions, this paper presents a comprehensive energy system economic operation strategy of Incineration power plant Power-to-gas (P2G) with waste heat recovery.
no code implementations • 4 Sep 2024 • Chaojun Xiao, Zhengyan Zhang, Chenyang Song, Dazhi Jiang, Feng Yao, Xu Han, Xiaozhi Wang, Shuo Wang, Yufei Huang, GuanYu Lin, Yingfa Chen, Weilin Zhao, Yuge Tu, Zexuan Zhong, Ao Zhang, Chenglei Si, Khai Hao Moo, Chenyang Zhao, Huimin Chen, Yankai Lin, Zhiyuan Liu, Jingbo Shang, Maosong Sun
We first formalize modules into emergent bricks - functional neuron partitions that emerge during the pre-training phase, and customized bricks - bricks constructed via additional post-training to improve the capabilities and knowledge of LLMs.
no code implementations • 1 Sep 2024 • Xiangxu Yu, Mindi Ruan, Chuanbo Hu, Wenqi Li, Lynn K. Paul, Xin Li, Shuo Wang
In this study, we present a quantitative and comprehensive analysis of social gaze in people with autism spectrum disorder (ASD).
no code implementations • CVPR 2025 • Yabiao Wang, Shuo Wang, Jiangning Zhang, Ke Fan, Jiafu Wu, Zhucun Xue, Yong liu
For temporal modeling, the single-person-based methods concatenate two people into a single one directly, while the separate modeling-based methods skip the modeling of interaction sequences.
no code implementations • 17 Aug 2024 • Shuo Wang, Yongcai Wang, Zhimin Xu, Yongyu Guo, Wanting Li, Zhe Huang, Xuewei Bai, Deying Li
GSLAMOT utilizes camera and LiDAR multimodal information as inputs and divides the representation of the dynamic scene into a semantic map for representing the static environment, a trajectory of the ego-agent, and an online maintained Tracklet Graph (TG) for tracking and predicting the 3D poses of the detected mobile objects.
1 code implementation • 15 Aug 2024 • Hanrui Wang, Shuo Wang, Cunjian Chen, Massimo Tistarelli, Zhe Jin
In this paper, we propose a multi-task adversarial attack algorithm called MTADV that are adaptable for multiple users or systems.
no code implementations • 14 Aug 2024 • Xiaoyang Yu, Youfang Lin, Shuo Wang, Kai Lv, Sheng Han
To further improve the training of extra UAS parameters, we introduce a Cross-Group Inverse (CGI) loss to predict other groups' agent policies with the trajectory information.
1 code implementation • 9 Aug 2024 • Weiqing Yang, Hanbin Wang, Zhenghao Liu, Xinze Li, Yukun Yan, Shuo Wang, Yu Gu, Minghe Yu, Zhiyuan Liu, Ge Yu
In this paper, we introduce DEBUGEVAL, a comprehensive benchmark for evaluating the debugging abilities of LLMs by emulating the multi-stage human debugging process.
1 code implementation • 2 Aug 2024 • Kunlun Zhu, Yifan Luo, Dingling Xu, Yukun Yan, Zhenghao Liu, Shi Yu, Ruobing Wang, Shuo Wang, Yishan Li, Nan Zhang, Xu Han, Zhiyuan Liu, Maosong Sun
However, evaluating the effectiveness of RAG systems in specialized scenarios remains challenging due to the high costs of data construction and the lack of suitable evaluation metrics.
1 code implementation • 1 Aug 2024 • Zhe Huang, Shuo Wang, Yongcai Wang, Wanting Li, Deying Li, Lei Wang
However, in collaborative perception, the quality of object detection based on a modality is highly sensitive to the relative pose errors among the agents.
1 code implementation • 24 Jul 2024 • Xingyu Zhu, Beier Zhu, Yi Tan, Shuo Wang, Yanbin Hao, Hanwang Zhang
Vision-language models such as CLIP are capable of mapping the different modality data into a unified feature space, enabling zero/few-shot inference by measuring the similarity of given images and texts.
no code implementations • 21 Jul 2024 • Yuan Liao, Jiang Bian, Yuhui Yun, Shuo Wang, Yubo Zhang, Jiaming Chu, Tao Wang, Kewei Li, Yuchen Li, Xuhong LI, Shilei Ji, Haoyi Xiong
While the field of NL2SQL has made significant advancements in translating natural language instructions into executable SQL scripts for data querying and processing, achieving full automation within the broader data science pipeline - encompassing data querying, analysis, visualization, and reporting - remains a complex challenge.
1 code implementation • 19 Jul 2024 • Jinda Lu, Shuo Wang, Yanbin Hao, Haifeng Liu, Xiang Wang, Meng Wang
However, these adaptation methods are usually operated on the global view of an input image, and thus biased perception of partial local details of the image.
1 code implementation • 16 Jul 2024 • Ouxiang Li, Yanbin Hao, Zhicai Wang, Bin Zhu, Shuo Wang, Zaixi Zhang, Fuli Feng
To alleviate these issues, leveraging on diffusion models' remarkable synthesis capabilities, we propose Diffusion-based Model Inversion (Diff-MI) attacks.
no code implementations • 16 Jul 2024 • Ruijie Yang, Yan Zhu, Peiyao Fu, Yizhe Zhang, Zhihua Wang, QuanLin Li, Pinghong Zhou, Xian Yang, Shuo Wang
To overcome this limitation, we introduce EndoFinder, a content-based image retrieval framework to find the 'digital twin' polyp in the reference database given a newly detected polyp.
no code implementations • 6 Jul 2024 • Binhao Ma, Tianhang Zheng, Hongsheng Hu, Di Wang, Shuo Wang, Zhongjie Ba, Zhan Qin, Kui Ren
Our evaluation demonstrates that unlearning this benign data, comprising no more than 1% of the total training data, can reduce model accuracy by up to 50%.
1 code implementation • 27 Jun 2024 • Zi Wang, Fanwen Wang, Chen Qin, Jun Lyu, Cheng Ouyang, Shuo Wang, Yan Li, Mengyao Yu, Haoyu Zhang, Kunyuan Guo, Zhang Shi, Qirong Li, Ziqiang Xu, Yajing Zhang, Hao Li, Sha Hua, Binghua Chen, Longyu Sun, Mengting Sun, Qin Li, Ying-Hua Chu, Wenjia Bai, Jing Qin, Xiahai Zhuang, Claudia Prieto, Alistair Young, Michael Markl, He Wang, Lianming Wu, Guang Yang, Xiaobo Qu, Chengyan Wang
To the best of our knowledge, the CMRxRecon2024 dataset is the largest and most protocal-diverse publicly available cardiac k-space dataset.
no code implementations • 18 Jun 2024 • Qin Li, Yizhe Zhang, Yan Li, Jun Lyu, Meng Liu, Longyu Sun, Mengting Sun, Qirong Li, Wenyue Mao, Xinran Wu, Yajing Zhang, Yinghua Chu, Shuo Wang, Chengyan Wang
We test state-of-the-art foundation models for medical image segmentation, including the original SAM, medical SAM and SAT models, to evaluate segmentation efficacy across different demographic groups and identify disparities.
1 code implementation • 18 Jun 2024 • Zhang Wan, Shuo Wang, Xudong Zhang
In this paper, we propose to inject prior knowledge to achieve a strong and efficient learner.
no code implementations • 17 Jun 2024 • Chen Sun, Tao Cui, Wenqi Zhang, Yingshuang Bai, Shuo Wang, Haojin Li
Combing Artificial Intelligence (AI) and wireless communication technologies has become one of the major technologies trends towards 2030.
1 code implementation • 13 Jun 2024 • Bowen Ping, Shuo Wang, Hanqing Wang, Xu Han, Yuzhuang Xu, Yukun Yan, Yun Chen, Baobao Chang, Zhiyuan Liu, Maosong Sun
Motivated by the long-tail distribution of singular values in the delta weights, we propose a delta quantization approach using mixed-precision.
1 code implementation • 13 Jun 2024 • Hanqing Wang, Yixia Li, Shuo Wang, Guanhua Chen, Yun Chen
It is observed that the minor matrix corresponds to the noisy or long-tail information, while the principal matrix contains important knowledge.
no code implementations • 3 Jun 2024 • Tianyu Huang, Tao Zhou, Weidi Xie, Shuo Wang, Qi Dou, Yizhe Zhang
We employ rectified annotations to perform online learning, with the aim of improving the segmentation quality of SA on medical images.
1 code implementation • 6 May 2024 • Haihong Hao, Shuo Wang, Huixia Ben, Yanbin Hao, Yansong Wang, Weiwei Wang
Specifically, we first process ME video frames and special frames or data parallelly by our cascaded Unimodal Space-Time Attention (USTA) to establish connections between subtle facial movements and specific facial areas.
Micro Expression Recognition
Micro-Expression Recognition
+1
1 code implementation • 3 May 2024 • Chuanbo Hu, Wenqi Li, Mindi Ruan, Xiangxu Yu, Shalaka Deshpande, Lynn K. Paul, Shuo Wang, Xin Li
Diagnosing language disorders associated with autism is a complex challenge, often hampered by the subjective nature and variability of traditional assessment methods.
no code implementations • 3 May 2024 • Chuanbo Hu, Jacob Thrasher, Wenqi Li, Mindi Ruan, Xiangxu Yu, Lynn K Paul, Shuo Wang, Xin Li
Diagnosing autism spectrum disorder (ASD) by identifying abnormal speech patterns from examiner-patient dialogues presents significant challenges due to the subtle and diverse manifestations of speech-related symptoms in affected individuals.
no code implementations • 15 Apr 2024 • Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Pranamesh Chakraborty, Sanjita Prajapati, Quan Kong, Norimasa Kobori, Munkhjargal Gochoo, Munkh-Erdene Otgonbold, Fady Alnajjar, Ganzorig Batnasan, Ping-Yang Chen, Jun-Wei Hsieh, Xunlei Wu, Sameer Satish Pusegaonkar, Yizhou Wang, Sujit Biswas, Rama Chellappa
The eighth AI City Challenge highlighted the convergence of computer vision and artificial intelligence in areas like retail, warehouse settings, and Intelligent Traffic Systems (ITS), presenting significant research opportunities.
1 code implementation • 12 Apr 2024 • Zhiwei Yang, Yucong Meng, Kexue Fu, Shuo Wang, Zhijian Song
When activating class objects, we argue that the false activation stems from the bias to the ambiguous regions during the feature extraction.
1 code implementation • 1 Apr 2024 • Jun Lyu, Chen Qin, Shuo Wang, Fanwen Wang, Yan Li, Zi Wang, Kunyuan Guo, Cheng Ouyang, Michael Tänzer, Meng Liu, Longyu Sun, Mengting Sun, Qin Li, Zhang Shi, Sha Hua, Hao Li, Zhensen Chen, Zhenlin Zhang, Bingyu Xin, Dimitris N. Metaxas, George Yiasemis, Jonas Teuwen, Liping Zhang, Weitian Chen, Yidong Zhao, Qian Tao, Yanwei Pang, Xiaohan Liu, Artem Razumov, Dmitry V. Dylov, Quan Dou, Kang Yan, Yuyang Xue, Yuning Du, Julia Dietlmeier, Carles Garcia-Cabrera, Ziad Al-Haj Hemidi, Nora Vogt, Ziqiang Xu, Yajing Zhang, Ying-Hua Chu, Weibo Chen, Wenjia Bai, Xiahai Zhuang, Jing Qin, Lianmin Wu, Guang Yang, Xiaobo Qu, He Wang, Chengyan Wang
To address this issue, we organized the Cardiac MRI Reconstruction Challenge (CMRxRecon) in 2023, in collaboration with the 26th International Conference on MICCAI.
no code implementations • 23 Mar 2024 • Xingyu Zhu, Shuo Wang, Jinda Lu, Yanbin Hao, Haifeng Liu, Xiangnan He
Few-shot learning (FSL) based on manifold regularization aims to improve the recognition capacity of novel objects with limited training samples by mixing two samples from different categories with a blending factor.
no code implementations • 23 Mar 2024 • Lanxin Xu, Shuo Wang
In this report, we introduce a novel self-supervised learning method for extracting latent embeddings from behaviors of larval zebrafish.
1 code implementation • 12 Mar 2024 • Erik Buchholz, Alsharif Abuadbba, Shuo Wang, Surya Nepal, Salil S. Kanhere
This work focuses on the systematisation of the state-of-the-art generative models for trajectories in the context of the proposed framework.
1 code implementation • CVPR 2024 • Zhiwei Yang, Kexue Fu, Minghong Duan, Linhao Qu, Shuo Wang, Zhijian Song
In this work, we devise a 'Separate and Conquer' scheme SeCo to tackle this issue from dimensions of image space and feature space.
1 code implementation • 25 Feb 2024 • Xinze Li, Zhenghao Liu, Chenyan Xiong, Shi Yu, Yukun Yan, Shuo Wang, Ge Yu
It finetunes the compression plugin module and uses the representations of gist tokens to emulate the raw prompts in the vanilla language model.
no code implementations • 21 Feb 2024 • Luming Lu, Jiyuan An, Yujie Wang, Liner Yang, Cunliang Kong, Zhenghao Liu, Shuo Wang, Haozhe Lin, Mingwei Fang, Yaping Huang, Erhong Yang
This paper presents the first text-to-CQL task that aims to automate the translation of natural language into CQL.
1 code implementation • 21 Feb 2024 • Meng Xu, Shuo Wang, Liner Yang, Haoyu Wang, Zhenghao Liu, Cunliang Kong, Yun Chen, Yang Liu, Maosong Sun, Erhong Yang
We evaluate several representative multilingual LLMs on the proposed OMGEval, which we believe will provide a valuable reference for the community to further understand and improve the multilingual capability of LLMs.
4 code implementations • 21 Feb 2024 • Xinrong Zhang, Yingfa Chen, Shengding Hu, Zihang Xu, JunHao Chen, Moo Khai Hao, Xu Han, Zhen Leng Thai, Shuo Wang, Zhiyuan Liu, Maosong Sun
Processing and reasoning over long contexts is crucial for many practical applications of Large Language Models (LLMs), such as document comprehension and agent construction.
1 code implementation • 21 Feb 2024 • Zhipeng Xu, Zhenghao Liu, Yukun Yan, Shuo Wang, Shi Yu, Zheni Zeng, Chaojun Xiao, Zhiyuan Liu, Ge Yu, Chenyan Xiong
Retrieval-Augmented Generation (RAG) enables Large Language Models (LLMs) to leverage external knowledge, enhancing their performance on knowledge-intensive tasks.
1 code implementation • 19 Feb 2024 • Yuanchi Zhang, Yile Wang, Zijun Liu, Shuo Wang, Xiaolong Wang, Peng Li, Maosong Sun, Yang Liu
While large language models (LLMs) have been pre-trained on multilingual corpora, their performance still lags behind in most languages compared to a few resource-rich languages.
1 code implementation • 18 Feb 2024 • Zhiyu Yang, Zihan Zhou, Shuo Wang, Xin Cong, Xu Han, Yukun Yan, Zhenghao Liu, Zhixing Tan, Pengyuan Liu, Dong Yu, Zhiyuan Liu, Xiaodong Shi, Maosong Sun
Scientific data visualization plays a crucial role in research by enabling the direct display of complex information and assisting researchers in identifying implicit patterns.
no code implementations • 18 Feb 2024 • Hanqing Wang, Bowen Ping, Shuo Wang, Xu Han, Yun Chen, Zhiyuan Liu, Maosong Sun
Most prior works on LoRA combination primarily rely on task-level weights for each involved LoRA, making different examples and tokens share the same LoRA weights.
1 code implementation • 17 Feb 2024 • Yuzhuang Xu, Xu Han, Zonghan Yang, Shuo Wang, Qingfu Zhu, Zhiyuan Liu, Weidong Liu, Wanxiang Che
Model quantification uses low bit-width values to represent the weight matrices of existing models to be quantized, which is a promising approach to reduce both storage and computational overheads of deploying highly anticipated LLMs.
1 code implementation • 7 Feb 2024 • Haoyu Wang, Shuo Wang, Yukun Yan, Xujia Wang, Zhiyu Yang, Yuzhuang Xu, Zhenghao Liu, Liner Yang, Ning Ding, Xu Han, Zhiyuan Liu, Maosong Sun
Different from previous works that simply translate English instructions, we consider both the language-specific and language-agnostic abilities of LLMs.
1 code implementation • 5 Feb 2024 • Haodong Lu, Dong Gong, Shuo Wang, Jason Xue, Lina Yao, Kristen Moore
To tackle these issues, we propose PrototypicAl Learning with a Mixture of prototypes (PALM) which models each class with multiple prototypes to capture the sample diversities, and learns more faithful and compact samples embeddings to enhance OOD detection.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
+1
1 code implementation • 27 Jan 2024 • Buqiang Xu, Xin Dai, Zhenghao Liu, Huiyuan Xie, Xiaoyuan Yi, Shuo Wang, Yukun Yan, Liner Yang, Yu Gu, Ge Yu
In this paper, we propose LegalDuet, which continuously pretrains language models to learn a more tailored embedding space for representing legal cases.
no code implementations • 17 Jan 2024 • Shuo Wang, Fan Jia, Yingfei Liu, Yucheng Zhao, Zehui Chen, Tiancai Wang, Chi Zhang, Xiangyu Zhang, Feng Zhao
This paper introduces the Stream Query Denoising (SQD) strategy as a novel approach for temporal modeling in high-definition map (HD-map) construction.
no code implementations • 2 Jan 2024 • Shuo Wang, Ge Cheng, Yun Zhang
Graph Neural Networks (GNNs) are widely applied across various domains, yet they perform poorly in deep layers.
no code implementations • 15 Dec 2023 • Yizhe Zhang, Shuo Wang, Tao Zhou, Qi Dou, Danny Z. Chen
Segmentation quality assessment (SQA) plays a critical role in the deployment of a medical image based AI system.
1 code implementation • 13 Dec 2023 • Bang Wu, He Zhang, Xiangwen Yang, Shuo Wang, Minhui Xue, Shirui Pan, Xingliang Yuan
These limitations call for an effective and comprehensive solution that detects and mitigates data misuse without requiring exact training data while respecting the proprietary nature of such data.
no code implementations • 12 Dec 2023 • Yuwei Guo, WenHao Zhang, Licheng Jiao, Shuang Wang, Shuo Wang, Fang Liu
Visible-infrared person re-identification (VI-ReID) aims to search the same pedestrian of interest across visible and infrared modalities.
1 code implementation • 8 Dec 2023 • Fangzhou Song, Bin Zhu, Yanbin Hao, Shuo Wang
Leveraging on the remarkable capabilities of foundation models (i. e., Llama2 and SAM), we propose to augment recipe and food image by extracting alignable information related to the counterpart.
no code implementations • 6 Dec 2023 • Xiaobo Hu, Youfang Lin, Hehe Fan, Shuo Wang, Zhihao Wu, Kai Lv
To this end, an agent needs to 1) learn a piece of certain knowledge about the relations of object categories in the world during training and 2) look for the target object based on the pre-learned object category relations and its moving trajectory in the current unseen environment.
no code implementations • 4 Dec 2023 • Xiaobo Hu, Youfang Lin, Yue Liu, Jinwen Wang, Shuo Wang, Hehe Fan, Kai Lv
Visual reinforcement learning has proven effective in solving control tasks with high-dimensional observations.
1 code implementation • 16 Nov 2023 • Hanbin Wang, Zhenghao Liu, Shuo Wang, Ganqu Cui, Ning Ding, Zhiyuan Liu, Ge Yu
INTERVENOR prompts Large Language Models (LLMs) to play distinct roles during the code repair process, functioning as both a Code Learner and a Code Teacher.
Ranked #32 on
Code Generation
on MBPP
1 code implementation • 6 Nov 2023 • Shuo Wang, Jing Li, Zibo Zhao, Dongze Lian, Binbin Huang, Xiaomei Wang, Zhengxin Li, Shenghua Gao
Holistic scene understanding includes semantic segmentation, surface normal estimation, object boundary detection, depth estimation, etc.
no code implementations • 27 Oct 2023 • Shuo Wang, Issei Sato
Furthermore, we show that the existing parameter saliency method exhibits a bias against the depth of layers in deep neural networks.
1 code implementation • 24 Oct 2023 • Yicheng Lin, Shuo Wang, Yunlong Jiang, Bin Han
Modifying the typical brightness consistency of the optical flow method to the convolutional feature consistency yields the light-robust hybrid optical flow method.
no code implementations • 20 Oct 2023 • Shuo Wang, Keke Gai, Jing Yu, Liehuang Zhu, Kim-Kwang Raymond Choo, Bin Xiao
Then the passive party, who owns only features of the sample, injects the blinding factor into the local embedding and sends it to the active party.
1 code implementation • 17 Oct 2023 • Shuo Wang, Yan Zhu, Xiaoyuan Luo, Zhiwei Yang, Yizhe Zhang, Peiyao Fu, Manning Wang, Zhijian Song, QuanLin Li, Pinghong Zhou, Yike Guo
EndoKED automates the transformation of raw colonoscopy records into image datasets with pixel-level annotation.
no code implementations • 2 Oct 2023 • Shuo Wang, Amiya Ranjan, Lawrence Jiang
The scarcity of high quality actions video data is a bottleneck in the research and application of action recognition.
no code implementations • 2 Oct 2023 • Shuo Wang, Carlos Crespo-Quinones
Translation of natural language into syntactically correct commands for data visualization is an important application of natural language models and could be leveraged to many different tasks.
2 code implementations • 19 Sep 2023 • Chengyan Wang, Jun Lyu, Shuo Wang, Chen Qin, Kunyuan Guo, Xinyu Zhang, Xiaotong Yu, Yan Li, Fanwen Wang, Jianhua Jin, Zhang Shi, Ziqiang Xu, Yapeng Tian, Sha Hua, Zhensen Chen, Meng Liu, Mengting Sun, Xutong Kuang, Kang Wang, Haoran Wang, Hao Li, Yinghua Chu, Guang Yang, Wenjia Bai, Xiahai Zhuang, He Wang, Jing Qin, Xiaobo Qu
However, a limitation of CMR is its slow imaging speed, which causes patient discomfort and introduces artifacts in the images.
no code implementations • 9 Sep 2023 • Yizhe Zhang, Shuo Wang, Yejia Zhang, Danny Z. Chen
Conformal prediction (CP) generates a set of predictions for a given test sample such that the prediction set almost always contains the true label (e. g., 99. 5\% of the time).
1 code implementation • 9 Sep 2023 • Yuzhuang Xu, Shuo Wang, Peng Li, Fuwen Luo, Xiaolong Wang, Weidong Liu, Yang Liu
Communication games, which we refer to as incomplete information games that heavily depend on natural language communication, hold significant research value in fields such as economics, social science, and artificial intelligence.
1 code implementation • 26 Aug 2023 • Yizhe Zhang, Tao Zhou, Shuo Wang, Ye Wu, Pengfei Gu, Danny Z. Chen
Our new method is iterative and consists of two main stages: (1) segmentation model training; (2) expanding the labeled set by using the trained segmentation model, an unlabeled set, SAM, and domain-specific knowledge.
1 code implementation • 14 Aug 2023 • Bo Dong, Jialun Pei, Rongrong Gao, Tian-Zhu Xiang, Shuo Wang, Huan Xiong
Due to the high similarity between camouflaged instances and the background, the recently proposed camouflaged instance segmentation (CIS) faces challenges in accurate localization and instance segmentation.
1 code implementation • 12 Jul 2023 • Yuzhuang Xu, Shuo Wang, Peng Li, Xuebo Liu, Xiaolong Wang, Weidong Liu, Yang Liu
Although neural machine translation (NMT) models perform well in the general domain, it remains rather challenging to control their generation behavior to satisfy the requirement of different users.
1 code implementation • 29 Jun 2023 • Shuo Wang, Terrence Tricco, Xianta Jiang, Charles Robertson, John Hawkin
This study can help improve the cognition of synthetic data and further explore the application of synthetic data generation in card fraud detection.
1 code implementation • 23 Jun 2023 • Nan Hu, Daobilige Su, Shuo Wang, Xuechang Wang, Huiyu Zhong, Zimeng Wang, Yongliang Qiao, Yu Tan
Regarding the robust tracking of vegetable plants, to solve the challenging problem of associating vegetables with similar color and texture in consecutive images, in this paper, a novel method of Multiple Object Tracking and Segmentation (MOTS) is proposed for instance segmentation and tracking of multiple vegetable plants.
1 code implementation • 5 Jun 2023 • Ruining Chong, Luming Lu, Liner Yang, Jinran Nie, Zhenghao Liu, Shuo Wang, Shuhan Zhou, Yaoxin Li, Erhong Yang
We hope to build a basic understanding of Chinese text simplification through the foundational work and provide references for future research.
no code implementations • 23 Apr 2023 • Hongyu Sun, Yongcai Wang, Xudong Cai, Peng Wang, Zhe Huang, Deying Li, Yu Shao, Shuo Wang
To advance the research and practical solutions for bird strike prevention, in this paper, we present a large-scale challenging dataset AirBirds that consists of 118, 312 time-series images, where a total of 409, 967 bounding boxes of flying birds are manually, carefully annotated.
no code implementations • 23 Apr 2023 • Wanting Li, Shuo Wang, Yongcai Wang, Yu Shao, Xuewei Bai, Deying Li
Using this compact line presentation, Inverse Depth Line SLAM (IDLS) is proposed to track the line features in SLAM in an accurate and efficient way.
1 code implementation • 22 Apr 2023 • Yizhe Zhang, Tao Zhou, Shuo Wang, Peixian Liang, Danny Z. Chen
Thus, how to utilize such a large foundation model for medical image segmentation is an emerging research target.
no code implementations • 20 Apr 2023 • Mindi Ruan, Xiangxu Yu, Na Zhang, Chuanbo Hu, Shuo Wang, Xin Li
How can we teach a computer to recognize 10, 000 different actions?
no code implementations • 15 Apr 2023 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Meenakshi S. Arya, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Sanjita Prajapati, Alice Li, Shangru Li, Krishna Kunadharaju, Shenxin Jiang, Rama Chellappa
The AI City Challenge's seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems (ITS) - that have considerable untapped potential.
1 code implementation • 11 Apr 2023 • Xue-Jing Luo, Shuo Wang, Zongwei Wu, Christos Sakaridis, Yun Cheng, Deng-Ping Fan, Luc van Gool
Specifically, we leverage the latent diffusion model to synthesize salient objects in camouflaged scenes, while using the zero-shot image classification ability of the Contrastive Language-Image Pre-training (CLIP) model to prevent synthesis failures and ensure the synthesized object aligns with the input prompt.
1 code implementation • CVPR 2023 • Zhou Huang, Hang Dai, Tian-Zhu Xiang, Shuo Wang, Huai-Xin Chen, Jie Qin, Huan Xiong
Vision transformers have recently shown strong global context modeling capabilities in camouflaged object detection.
1 code implementation • CVPR 2023 • Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang, Xiangnan He
It is well-known that zero-shot learning (ZSL) can suffer severely from the problem of domain shift, where the true and learned data distributions for the unseen classes do not match.
no code implementations • 7 Mar 2023 • Xin Li, Shuo Wang
It has been hypothesized that the ventral stream processing for object recognition is based on a mechanism called cortically local subspace untangling.
no code implementations • CVPR 2023 • Shuo Wang, Xinhai Zhao, Hai-Ming Xu, Zehui Chen, Dameng Yu, Jiahao Chang, Zhen Yang, Feng Zhao
Based on the covariate shift assumption, we find that the gap mainly attributes to the feature distribution of BEV, which is determined by the quality of both depth estimation and 2D image's feature representation.
2 code implementations • 28 Feb 2023 • Peng Zheng, Jie Qin, Shuo Wang, Tian-Zhu Xiang, Huan Xiong
To learn better group consensus, we propose the Group Consensus Aggregation Module (GCAM) to abstract the common features of each image group; meanwhile, to make the consensus representation more discriminative, we introduce the Memory-based Contrastive Module (MCM), which saves and updates the consensus of images from different groups in a queue of memories.
no code implementations • 20 Feb 2023 • Jing Xu, Shuo Wang, Na Ying, Xiao Xiao, Jiang Zhang, Yun Cheng, Zhiling Jin, Gangfeng Zhang
Previous GCNs-based methods usually require providing spatial correlation graph structure of observation sites in advance.
no code implementations • 2 Feb 2023 • Meng Zhao, Yifan Hu, Ruixuan Jiang, Yuanli Zhao, Dong Zhang, Yan Zhang, Rong Wang, Yong Cao, Qian Zhang, Yonggang Ma, Jiaxi Li, Shaochen Yu, Wenjie Li, Ran Zhang, Yefeng Zheng, Shuo Wang, Jizong Zhao
Conclusions: The proposed deep learning algorithms can be an effective tool for early identification of hemorrhage etiologies based on NCCT scans.
1 code implementation • 30 Jan 2023 • Mengyun Qiao, Shuo Wang, Huaqi Qiu, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Wenjia Bai
Two key questions in cardiac image analysis are to assess the anatomy and motion of the heart from images; and to understand how they are associated with non-imaging clinical factors such as gender, age and diseases.
no code implementations • ICCV 2023 • Linhao Qu, Zhiwei Yang, Minghong Duan, Yingfan Ma, Shuo Wang, Manning Wang, Zhijian Song
However, there are still three important issues that have not been fully addressed: (1) positive bags with a low positive instance ratio are prone to the influence of a large number of negative instances; (2) the correlation between local and global features of pathology images has not been fully modeled; and (3) there is a lack of effective information interaction between different magnifications.
1 code implementation • ICCV 2023 • Zehui Chen, Zhenyu Li, Shuo Wang, Dengpan Fu, Feng Zhao
To this end, we propose NoiseDet, a simple yet effective framework for semi-supervised 3D object detection.
no code implementations • 23 Dec 2022 • Haoran Wang, Yan Zhu, Wenzheng Qin, Yizhe Zhang, Pinghong Zhou, QuanLin Li, Shuo Wang, Zhijian Song
In addition, the released dataset can be used to perform 'stress' tests on established detection systems and encourages further research toward robust and reliable computer-aided endoscopic image analysis.
1 code implementation • ICCV 2023 • Zongwei Wu, Danda Pani Paudel, Deng-Ping Fan, Jingjing Wang, Shuo Wang, Cédric Demonceaux, Radu Timofte, Luc van Gool
In this work, we adapt such depth inference models for object segmentation using the objects' "pop-out" prior in 3D.
no code implementations • 24 Nov 2022 • Seonhye Park, Alsharif Abuadbba, Shuo Wang, Kristen Moore, Yansong Gao, Hyoungshick Kim, Surya Nepal
In this study, we introduce DeepTaster, a novel DNN fingerprinting technique, to address scenarios where a victim's data is unlawfully used to build a suspect model.
no code implementations • ICCV 2023 • Jiahao Chang, Shuo Wang, HaiMing Xu, Zehui Chen, Chenhongyi Yang, Feng Zhao
Next, we propose a target-aware feature distillation to help the student model learn from the object-centric features of the teacher model.
no code implementations • 11 Nov 2022 • Jiarui Xing, Shuo Wang, Kenneth C. Bilchick, Frederick H. Epstein, Amit R. Patel, Miaomiao Zhang
With a newly introduced auxiliary LMA region classification sub-network, our proposed model shows more robustness to the complex pattern cause by myocardial scar, significantly eliminates their negative effects in LMA detection, and in turn improves the performance of scar classification.
no code implementations • 11 Nov 2022 • Jiarui Xing, Shuo Wang, Kenneth C. Bilchick, Amit R. Patel, Miaomiao Zhang
Automated identification of myocardial scar from late gadolinium enhancement cardiac magnetic resonance images (LGE-CMR) is limited by image noise and artifacts such as those related to motion and partial volume effect.
1 code implementation • 12 Oct 2022 • Shuo Wang, Chen Qin, Chengyan Wang, Kang Wang, Haoran Wang, Chen Chen, Cheng Ouyang, Xutong Kuang, Chengliang Dai, Yuanhan Mo, Zhang Shi, Chenchen Dai, Xinrong Chen, He Wang, Wenjia Bai
The quality of cardiac magnetic resonance (CMR) imaging is susceptible to respiratory motion artifacts.
1 code implementation • 28 Aug 2022 • Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu, Shuo Wang, Yi Guo, Yuanyuan Wang, Paul M. Matthews, Daniel Rueckert, Wenjia Bai
Understanding the morphological and functional changes of the heart during ageing is a key scientific question, the answer to which will help us define important risk factors of cardiovascular disease and monitor disease progression.
1 code implementation • 4 Aug 2022 • Cheng Ouyang, Shuo Wang, Chen Chen, Zeju Li, Wenjia Bai, Bernhard Kainz, Daniel Rueckert
In image segmentation, well-calibrated probabilities allow radiologists to identify regions where model-predicted segmentations are unreliable.
1 code implementation • 15 Jul 2022 • Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu, Xiangnan He
They use token-mixing layers to capture cross-token interactions, as opposed to the multi-head self-attention mechanism used by Transformers.
1 code implementation • 4 Jul 2022 • Chang Liu, Gang Yang, Shuo Wang, Hangxu Wang, Yunhua Zhang, Yutao Wang
We employ the powerful feature extraction capability of Transformer (PVTv2) to extract global semantic information from RGB data and design a lightweight CNN backbone (LWDepthNet) to extract spatial structure information from depth data without pre-training.
no code implementations • 3 Jul 2022 • Lin Li, Jingyi Liu, Shuo Wang, Xunkun Wang, Tian-Zhu Xiang
Trichomoniasis is a common infectious disease with high incidence caused by the parasite Trichomonas vaginalis, increasing the risk of getting HIV in humans if left untreated.
1 code implementation • 2 Jul 2022 • Yujia Sun, Shuo Wang, Chenglizhao Chen, Tian-Zhu Xiang
Camouflaged object detection (COD), segmenting objects that are elegantly blended into their surroundings, is a valuable yet challenging task.
1 code implementation • 8 Jun 2022 • Chen Qin, Shuo Wang, Chen Chen, Wenjia Bai, Daniel Rueckert
In contrast to most existing approaches which impose explicit generic regularization such as smoothness, in this work we propose a novel method that can implicitly learn an application-specific biomechanics-informed prior and embed it into a neural network-parameterized transformation model.
no code implementations • 2 Jun 2022 • Chengliang Dai, Shuo Wang, Yuanhan Mo, Elsa Angelini, Yike Guo, Wenjia Bai
We evaluate the framework on two different brain image analysis tasks, namely brain tumour segmentation and whole brain segmentation.
1 code implementation • 23 May 2022 • Shuo Wang, Peng Li, Zhixing Tan, Zhaopeng Tu, Maosong Sun, Yang Liu
In this work, we propose a template-based method that can yield results with high translation quality and match accuracy and the inference speed of our method is comparable with unconstrained NMT models.
no code implementations • 20 May 2022 • Wenxuan Wang, Wenxiang Jiao, Shuo Wang, Zhaopeng Tu, Michael R. Lyu
Zero-shot translation is a promising direction for building a comprehensive multilingual neural machine translation~(MNMT) system.
no code implementations • 11 May 2022 • Xiaoqin Zhang, Ziwei Huang, Jingjing Zheng, Shuo Wang, Xianta Jiang
The task of grasp pattern recognition aims to derive the applicable grasp types of an object according to the visual information.
no code implementations • 5 May 2022 • Weichen Fan, Yuanbo Yang, Kunpeng Qiu, Shuo Wang, Yongxin Guo
Therefore, to address the generalization problem in GI(Gastrointestinal) endoscopy, we propose a multi-domain GI dataset and a light, plug-in block called InvNorm(Invertible Normalization), which could achieve a better generalization performance in any structure.
1 code implementation • 23 Apr 2022 • Wei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora Salim
To address these issues, we construct new graph models to represent the contextual information of each node and the long-term spatio-temporal data dependency structure.
2 code implementations • 21 Apr 2022 • Milind Naphade, Shuo Wang, David C. Anastasiu, Zheng Tang, Ming-Ching Chang, Yue Yao, Liang Zheng, Mohammed Shaiqur Rahman, Archana Venkatachalapathy, Anuj Sharma, Qi Feng, Vitaly Ablavsky, Stan Sclaroff, Pranamesh Chakraborty, Alice Li, Shangru Li, Rama Chellappa
The four challenge tracks of the 2022 AI City Challenge received participation requests from 254 teams across 27 countries.
1 code implementation • 20 Apr 2022 • Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu, Xiangnan He
Attention mechanisms have significantly boosted the performance of video classification neural networks thanks to the utilization of perspective contexts.
1 code implementation • 17 Apr 2022 • Mohammed Shaiqur Rahman, Jiyang Wang, Senem Velipasalar Gursoy, David Anastasiu, Shuo Wang, Anuj Sharma
This article presents a synthetic distracted driving (SynDD2 - a continuum of SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones.
no code implementations • 3 Apr 2022 • Alsharif Abuadbba, Shuo Wang, Mahathir Almashor, Muhammed Ejaz Ahmed, Raj Gaire, Seyit Camtepe, Surya Nepal
However, with an average of 10K phishing links reported per hour to platforms such as PhishTank and VirusTotal (VT), the deficiencies of such ML-based solutions are laid bare.
no code implementations • 26 Mar 2022 • Sha Yuan, Hanyu Zhao, Shuai Zhao, Jiahong Leng, Yangxiao Liang, Xiaozhi Wang, Jifan Yu, Xin Lv, Zhou Shao, Jiaao He, Yankai Lin, Xu Han, Zhenghao Liu, Ning Ding, Yongming Rao, Yizhao Gao, Liang Zhang, Ming Ding, Cong Fang, Yisen Wang, Mingsheng Long, Jing Zhang, Yinpeng Dong, Tianyu Pang, Peng Cui, Lingxiao Huang, Zheng Liang, HuaWei Shen, HUI ZHANG, Quanshi Zhang, Qingxiu Dong, Zhixing Tan, Mingxuan Wang, Shuo Wang, Long Zhou, Haoran Li, Junwei Bao, Yingwei Pan, Weinan Zhang, Zhou Yu, Rui Yan, Chence Shi, Minghao Xu, Zuobai Zhang, Guoqiang Wang, Xiang Pan, Mengjie Li, Xiaoyu Chu, Zijun Yao, Fangwei Zhu, Shulin Cao, Weicheng Xue, Zixuan Ma, Zhengyan Zhang, Shengding Hu, Yujia Qin, Chaojun Xiao, Zheni Zeng, Ganqu Cui, Weize Chen, Weilin Zhao, Yuan YAO, Peng Li, Wenzhao Zheng, Wenliang Zhao, Ziyi Wang, Borui Zhang, Nanyi Fei, Anwen Hu, Zenan Ling, Haoyang Li, Boxi Cao, Xianpei Han, Weidong Zhan, Baobao Chang, Hao Sun, Jiawen Deng, Chujie Zheng, Juanzi Li, Lei Hou, Xigang Cao, Jidong Zhai, Zhiyuan Liu, Maosong Sun, Jiwen Lu, Zhiwu Lu, Qin Jin, Ruihua Song, Ji-Rong Wen, Zhouchen Lin, LiWei Wang, Hang Su, Jun Zhu, Zhifang Sui, Jiajun Zhang, Yang Liu, Xiaodong He, Minlie Huang, Jian Tang, Jie Tang
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.
1 code implementation • ACL 2022 • Shuo Wang, Zhixing Tan, Yang Liu
In this work, we propose to open this black box by directly integrating the constraints into NMT models.
1 code implementation • 22 Mar 2022 • Xiaobin Hu, Shuo Wang, Xuebin Qin, Hang Dai, Wenqi Ren, Ying Tai, Chengjie Wang, Ling Shao
Spotting camouflaged objects that are visually assimilated into the background is tricky for both object detection algorithms and humans who are usually confused or cheated by the perfectly intrinsic similarities between the foreground objects and the background surroundings.