no code implementations • ACL 2022 • Juncai Guo, Jin Liu, Yao Wan, Li Li, Pingyi Zhou
In this paper, we propose CODESCRIBE to model the hierarchical syntax structure of code by introducing a novel triplet position for code summarization.
no code implementations • 17 Apr 2025 • Guanyu Wang, Kailong Wang, Yihao Huang, Mingyi Zhou, Zhang Qing cnwatcher, Geguang Pu, Li Li
The rapid advancement of diffusion models and personalization techniques has made it possible to recreate individual portraits from just a few publicly available images.
no code implementations • 6 Apr 2025 • Cheng Chang, Jingwei Ge, Jiazhe Guo, Zelin Guo, Binghong Jiang, Li Li
Driving scenario data play an increasingly vital role in the development of intelligent vehicles and autonomous driving.
1 code implementation • 3 Apr 2025 • Yi Nian, Shenzhe Zhu, Yuehan Qin, Li Li, Ziyi Wang, Chaowei Xiao, Yue Zhao
Multimodal large language models (MLLMs) excel in vision-language tasks but also pose significant risks of generating harmful content, particularly through jailbreak attacks.
no code implementations • 29 Mar 2025 • Binchuan Qi, Wei Gong, Li Li
In this paper, we adopt a probability distribution estimation perspective to explore the optimization mechanisms of supervised classification using deep neural networks.
1 code implementation • 27 Mar 2025 • Hanyue Tu, Siqi Wu, Li Li, Wengang Zhou, Houqiang Li
Autoencoder-based structures have dominated recent learned image compression methods.
1 code implementation • 24 Mar 2025 • Ruixiao Dong, Mengde Xu, Zigang Geng, Li Li, Han Hu, Shuyang Gu
Current generative models, such as autoregressive and diffusion approaches, decompose high-dimensional data distribution learning into a series of simpler subtasks.
no code implementations • 24 Mar 2025 • Bojun Liu, Yangzhi Ma, Ao Luo, Li Li, Dong Liu
To overcome this issue, we introduce a stage-wise Space-to-Channel (S2C) context model for both dense point clouds and low-level sparse point clouds.
1 code implementation • 15 Mar 2025 • Yebo Wu, Chunlin Tian, Jingguang Li, He Sun, Kahou Tam, Li Li, Chengzhong Xu
Large Language Models (LLMs) have achieved remarkable success across a wide range of tasks, with fine-tuning playing a pivotal role in adapting them to specific downstream applications.
no code implementations • 11 Mar 2025 • Mingyue Cheng, Yucong Luo, Jie Ouyang, Qi Liu, Huijie Liu, Li Li, Shuo Yu, Bohou Zhang, Jiawei Cao, Jie Ma, Daoyu Wang
Retrieval-Augmented Generation (RAG) has gained significant attention in recent years for its potential to enhance natural language understanding and generation by combining large-scale retrieval systems with generative models.
no code implementations • 10 Mar 2025 • Ming Wang, Fang Wang, Minghao Hu, Li He, Haiyang Wang, Jun Zhang, Tianwei Yan, Li Li, Zhunchen Luo, Wei Luo, Xiaoying Bai, Guotong Geng
Long-form article generation (LFAG) presents challenges such as maintaining logical consistency, comprehensive topic coverage, and narrative coherence across extended articles.
1 code implementation • 8 Mar 2025 • Li Li, Jiashu Qu, Yuxiao Zhou, Yuehan Qin, Tiankai Yang, Yue Zhao
To address this, we construct a causal graph for VLMs and employ counterfactual analysis to estimate the Natural Direct Effect (NDE) of vision, text, and their cross-modal interaction on the output.
2 code implementations • 2 Mar 2025 • Wenke E, Chao Yuan, Li Li, Yixin Sun, Yona Falinie A. Gaus, Amir Atapour-Abarghouei, Toby P. Breckon
We present Dur360BEV, a novel spherical camera autonomous driving dataset equipped with a high-resolution 128-channel 3D LiDAR and a RTK-refined GNSS/INS system, along with a benchmark architecture designed to generate Bird-Eye-View (BEV) maps using only a single spherical camera.
1 code implementation • 27 Feb 2025 • Xuyang Wei, Chunlin Tian, Li Li
Effective instruction fine-tuning on diverse image-text datasets is crucial for developing a versatile Multimodal Large Language Model (MLLM), where dataset composition dictates the model's adaptability across multimodal tasks.
no code implementations • 13 Feb 2025 • Minghong Wu, Minghui LiWang, Yuhan Su, Li Li, Seyyedali Hosseinalipour, Xianbin Wang, Huaiyu Dai, Zhenzhen Jiao
Current research on HFL mainly focus on enhancing model accuracy, latency, and energy consumption in scenarios with a stable/fixed set of clients.
no code implementations • 23 Jan 2025 • Yuhui Yun, Huilong Ye, Xinru Li, Ruojia Li, Jingfeng Deng, Li Li, Haoyi Xiong
The paper introduces EICopilot, an novel agent-based solution enhancing search and exploration of enterprise registration data within extensive online knowledge graphs like those detailing legal entities, registered capital, and major shareholders.
no code implementations • 20 Dec 2024 • Yiheng Jiang, Haotian Zhang, Li Li, Dong Liu, Zhu Li
In this paper, motivated by the recent success of learned image compression, we propose a new framework that uses sparse point clouds to assist in learned image compression in the autonomous driving scenario.
no code implementations • 16 Dec 2024 • Li Li
This paper provides a comprehensive review of the impact of AE attacks on key cybersecurity applications, highlighting both their theoretical and practical implications.
no code implementations • 1 Dec 2024 • Yue Liu, Chakkrit Tantithamthavorn, Li Li
Recent years have witnessed the emerging trend of extensions in modern Integrated Development Environments (IDEs) like Visual Studio Code (VSCode) that significantly enhance developer productivity.
no code implementations • 30 Nov 2024 • Weian Guo, Wuzhao Li, Li Li, Lun Zhang, Dongyang Li
Addressing these challenges, this paper presents a novel temporal-aware multi-objective robust optimization framework, which for the first time formally incorporates temporal continuity into the optimization of dynamic multi-hop VANETs.
no code implementations • 28 Nov 2024 • Haotian Zhang, Li Li, Dong Liu
Probabilistic models with more parameters, such as the Gaussian mixture models, can fit the distribution of latent variables more precisely, but the corresponding complexity is higher.
no code implementations • 19 Nov 2024 • Shuiying Liao, P. Y. Mok, Li Li
This paper reports on the development of a Consistency Regularized model for Bayesian Personalized Ranking (CR-BPR), addressing to the drawbacks in existing complementary clothing recommendation methods, namely limited consistency and biased learning caused by diverse feature scale of multi-modal data.
no code implementations • 15 Nov 2024 • Zhendong Liu, Yi Nian, Henry Peng Zou, Li Li, Xiyang Hu, Yue Zhao
Existing OOD detection methods struggle to capture the intricate semantic relationships and label co-occurrences inherent in multi-label settings, often requiring large amounts of training data and failing to generalize to unseen label combinations.
no code implementations • 5 Nov 2024 • Weian Guo, Ruizhi Sha, Li Li, Lun Zhang, Dongyang Li
To alleviate computational load on RSUs and cloud platforms, reduce communication bandwidth requirements, and provide a more stable vehicular network service, this paper proposes an optimized pinning control approach for heterogeneous multi-network vehicular ad-hoc networks (VANETs).
3 code implementations • 1 Nov 2024 • Li Li
3D LiDAR point cloud data is crucial for scene perception in computer vision, robotics, and autonomous driving.
no code implementations • 1 Nov 2024 • Song Yu, Xiaofei Xu, Fangfei Xu, Li Li
In this work, we propose a framework to improve the performance of large language models for TCM tasks using only a small amount of data.
no code implementations • 12 Oct 2024 • Chunlin Tian, Li Li, Kahou Tam, Yebo Wu, Chengzhong Xu
In this paper, we propose SmartSplit, a framework that effectively reduces the memory footprint on the device side while guaranteeing the training progress and model accuracy for heterogeneous FL through model splitting. Towards this end, SmartSplit employs a hierarchical structure to adaptively guide the overall training process.
no code implementations • 8 Oct 2024 • Binchuan Qi, Wei Gong, Li Li
This paper introduces an optimization framework aimed at providing a theoretical foundation for a class of composite optimization problems, particularly those encountered in deep learning.
no code implementations • 30 Sep 2024 • Yinzheng Zhao, Zhihao Zhao, Junjie Yang, Li Li, M. Ali Nasseri, Daniel Zapp
Results: There were 279 (12. 38%) images in normal group and 384 (16. 23%) images in the high myopia group.
no code implementations • 23 Sep 2024 • Li Li, Mingyue Cheng, Zhiding Liu, Hao Zhang, Qi Liu, Enhong Chen
The algorithm operates in two stages: in the first stage, we fine-tune the pre-trained language model on the recommendation dataset to transfer the pre-trained knowledge to the recommendation task; in the second stage, we distill the trained language model to transfer the learned knowledge to a lightweight model.
no code implementations • 21 Sep 2024 • ZhiHao Lin, Wei Ma, Mingyi Zhou, Yanjie Zhao, Haoyu Wang, Yang Liu, Jun Wang, Li Li
During our manual attempts to perform jailbreak attacks, we found that the vocabulary of the response of the target model gradually became richer and eventually produced harmful responses.
no code implementations • 21 Sep 2024 • Yuxuan Zhu, Shiyi Wang, Wenqing Zhong, Nianchen Shen, Yunqi Li, Siqi Wang, Zhiheng Li, Cathy Wu, Zhengbing He, Li Li
We further analyze the potential limitations and challenges that LLMs may encounter in promoting the development of AD technology.
no code implementations • 20 Sep 2024 • Weian Guo, Wuzhao Li, Zhiou Zhang, Lun Zhang, Li Li, Dongyang Li
This paper presents a scalable multi-objective optimization approach for robust traffic signal control in dynamic and uncertain urban environments.
no code implementations • 17 Sep 2024 • Tianyu Zhang, Haotian Zhang, Yuqi Li, Li Li, Dong Liu
Learned image compression (LIC) has achieved state-of-the-art rate-distortion performance, deemed promising for next-generation image compression techniques.
no code implementations • 13 Sep 2024 • Zhuoyuan Li, Junqi Liao, Chuanbo Tang, Haotian Zhang, Yuqi Li, Yifan Bian, Xihua Sheng, Xinmin Feng, Yao Li, Changsheng Gao, Li Li, Dong Liu, Feng Wu
Image/video coding has been a remarkable research area for both academia and industry for many years.
no code implementations • 11 Sep 2024 • Shichen Zhan, Yebo Wu, Chunlin Tian, Yan Zhao, Li Li
However, large memory footprint and high energy consumption during the training process excludes the low-end devices from contributing to the global model with their own data, which severely deteriorates the model performance in real-world scenarios.
no code implementations • 6 Sep 2024 • Yizhen Zheng, Huan Yee Koh, Maddie Yang, Li Li, Lauren T. May, Geoffrey I. Webb, Shirui Pan, George Church
The integration of Large Language Models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding disease mechanisms, facilitating drug discovery, and optimizing clinical trial processes.
no code implementations • 25 Aug 2024 • Li Li, Tanqiu Qiao, Hubert P. H. Shum, Toby P. Breckon
3D point clouds are essential for perceiving outdoor scenes, especially within the realm of autonomous driving.
1 code implementation • 25 Aug 2024 • Keyi Zhou, Li Li, Wengang Zhou, Yonghui Wang, Hao Feng, Houqiang Li
In this work, we propose LaneTCA to bridge the individual video frames and explore how to effectively aggregate the temporal context.
no code implementations • 16 Aug 2024 • Xihua Sheng, Li Li, Dong Liu, Shiqi Wang
In this paper, we introduce a bi-directional deep contextual video compression scheme tailored for B-frames, termed DCVC-B, to improve the compression performance of deep B-frame coding.
1 code implementation • 9 Aug 2024 • Zhibo Zhang, Wuxia Bai, Yuxi Li, Mark Huasong Meng, Kailong Wang, Ling Shi, Li Li, Jun Wang, Haoyu Wang
In this work, we aim to enhance the understanding of glitch tokens and propose techniques for their detection and mitigation.
1 code implementation • 7 Aug 2024 • Yonghui Wang, Shaokai Liu, Li Li, Wengang Zhou, Houqiang Li
In this case, when the color of the object is similar to that of the shadow, existing methods struggle to achieve accurate detection.
no code implementations • 2 Aug 2024 • Zhensu Sun, Haotian Zhu, Bowen Xu, Xiaoning Du, Li Li, David Lo
Inspired by their remarkable capabilities in understanding and generating code, we propose to deal with the runtime errors in a real-time manner using LLMs.
no code implementations • 28 Jul 2024 • Xihua Sheng, Chuanbo Tang, Li Li, Dong Liu, Feng Wu
Based on a small baseline model, we gradually scale up the model sizes of its different coding parts, including the motion encoder-decoder, motion entropy model, contextual encoder-decoder, contextual entropy model, and temporal context mining module, and analyze the influence of model sizes on video compression performance.
no code implementations • 25 Jul 2024 • Haicheng Liao, Haoyu Sun, Huanming Shen, Chengyue Wang, Kahou Tam, Chunlin Tian, Li Li, Chengzhong Xu, Zhenning Li
To capture a wider range of visual cues, we further propose a multi-layer fusion that dynamically computes the temporal dependencies between different scenes and iteratively updates the correlations between different visual features for accurate and timely accident prediction.
no code implementations • 23 Jul 2024 • Haicheng Liao, Yongkang Li, Chengyue Wang, Yanchen Guan, Kahou Tam, Chunlin Tian, Li Li, Chengzhong Xu, Zhenning Li
As autonomous driving systems increasingly become part of daily transportation, the ability to accurately anticipate and mitigate potential traffic accidents is paramount.
no code implementations • 16 Jul 2024 • Zhuoyuan Li, Yao Li, Chuanbo Tang, Li Li, Dong Liu, Feng Wu
To address these issues, we introduce a uniformly accelerated motion model (UAMM) to exploit motion-related elements (velocity, acceleration) of moving objects between the video frames, and further combine them to assist the inter prediction methods to handle the variable motion in the temporal domain.
no code implementations • 15 Jul 2024 • Xuhong Wang, Haoyu Jiang, Yi Yu, Jingru Yu, Yilun Lin, Ping Yi, Yingchun Wang, Yu Qiao, Li Li, Fei-Yue Wang
Large Language Models (LLMs) are increasingly integrated into diverse industries, posing substantial security risks due to unauthorized replication and misuse.
no code implementations • 15 Jul 2024 • Zhuoyuan Li, Jiacheng Li, Yao Li, Li Li, Dong Liu, Feng Wu
Recently, neural network-based in-loop filtering methods achieve remarkable coding gains beyond the capability of advanced video coding standards, which becomes a powerful coding tool candidate for future video coding standards.
1 code implementation • 14 Jul 2024 • Li Li, Hubert P. H. Shum, Toby P. Breckon
To effectively embed high-dimensional RAPiD features, we propose a double-nested autoencoder structure with a novel class-aware embedding objective to encode high-dimensional features into manageable voxel-wise embeddings.
1 code implementation • 9 Jul 2024 • Renjie Liang, Li Li, Chongzhi Zhang, Jing Wang, Xizhou Zhu, Aixin Sun
To facilitate research in RVMR, we develop the TVR-Ranking dataset, based on the raw videos and existing moment annotations provided in the TVR dataset.
no code implementations • 7 Jul 2024 • Qi Sun, Hang Zhou, Wengang Zhou, Li Li, Houqiang Li
Synthesizing realistic 3D indoor scenes is a challenging task that traditionally relies on manual arrangement and annotation by expert designers.
no code implementations • 29 Jun 2024 • Junqi Liao, Yao Li, Zhuoyuan Li, Li Li, Dong Liu
To begin with, we improve the accuracy of temporal features by integrating feature-domain motion estimation into the IVCA framework, which allows for a more nuanced understanding of motion across frames.
no code implementations • 20 Jun 2024 • Xihua Sheng, Li Li, Dong Liu, Houqiang Li
With these filters, our codec can adapt to different reference qualities, making it easier to achieve the target reconstruction quality and reduce the reconstruction error propagation.
1 code implementation • International Conference on 3D Vision (3DV) 2021 • Li Li, Khalid N. Ismail, Hubert P. H. Shum, Toby P. Breckon
We present DurLAR, a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery, as well as a sample benchmark task using depth estimation for autonomous driving applications.
no code implementations • 9 Jun 2024 • Mingwei Tang, Meng Liu, Hong Li, Junjie Yang, Chenglin Wei, Boyang Li, Dai Li, Rengan Xu, Yifan Xu, Zehua Zhang, Xiangyu Wang, Linfeng Liu, Yuelei Xie, Chengye Liu, Labib Fawaz, Li Li, Hongnan Wang, Bill Zhu, Sri Reddy
In recommendation systems, high-quality user embeddings can capture subtle preferences, enable precise similarity calculations, and adapt to changing preferences over time to maintain relevance.
no code implementations • 5 Jun 2024 • Kahou Tam, Kewei Xu, Li Li, Huazhu Fu
Federated Learning (FL) has evolved as a powerful tool for collaborative model training across multiple entities, ensuring data privacy in sensitive sectors such as healthcare and finance.
1 code implementation • 23 May 2024 • Jiahao Sun, Chunmei Qing, Xiang Xu, Lingdong Kong, Youquan Liu, Li Li, Chenming Zhu, Jingwei Zhang, Zeqi Xiao, Runnan Chen, Tai Wang, Wenwei Zhang, Kai Chen
In the rapidly evolving field of autonomous driving, precise segmentation of LiDAR data is crucial for understanding complex 3D environments.
no code implementations • 21 May 2024 • Wei Ji, Li Li, Zheqi Lv, Wenqiao Zhang, Mengze Li, Zhen Wan, Wenqiang Lei, Roger Zimmermann
As these systems grapple with shifting data distributions between the cloud and devices, the traditional approach of fine-tuning-based adaptation (FTA) exists the following issues: the costly and time-consuming data annotation required by FTA and the looming risk of model overfitting.
no code implementations • 10 May 2024 • Pengcheng Zhu, Yaoming Zhuang, Baoquan Chen, Li Li, Chengdong Wu, Zhanlin Liu
This letter introduces a novel framework for dense Visual Simultaneous Localization and Mapping (VSLAM) based on Gaussian Splatting.
1 code implementation • 10 May 2024 • Zhiyuan Ning, Chunlin Tian, Meng Xiao, Wei Fan, Pengyang Wang, Li Li, Pengfei Wang, Yuanchun Zhou
Federated Learning faces significant challenges in statistical and system heterogeneity, along with high energy consumption, necessitating efficient client selection strategies.
no code implementations • 7 May 2024 • Chunlin Tian, Zhan Shi, Xinpeng Qin, Li Li, Chengzhong Xu
Federated Learning (FL) enables multiple devices to collaboratively train a shared model while ensuring data privacy.
no code implementations • 7 May 2024 • Changsheng Gao, Yiheng Jiang, Li Li, Dong Liu, Feng Wu
To maintain the feature discriminability of reconstructed features, we introduce a discrimination metric for feature compression.
no code implementations • 2 May 2024 • Yin Huang, Yongqi Dong, Youhua Tang, Li Li
The escalation in urban private car ownership has worsened the urban parking predicament, necessitating effective parking availability prediction for urban planning and management.
1 code implementation • 30 Apr 2024 • Chunlin Tian, Zhan Shi, Zhijiang Guo, Li Li, Chengzhong Xu
Through a series of experiments, we have uncovered two critical insights that shed light on the training and parameter inefficiency of LoRA.
1 code implementation • 25 Apr 2024 • Zhensu Sun, Xiaoning Du, Zhou Yang, Li Li, David Lo
To improve inference efficiency and reduce computational costs, we propose the concept of AI-oriented grammar.
no code implementations • 20 Apr 2024 • Yebo Wu, Li Li, Chunlin Tian, Chengzhong Xu
In order to preserve the feature representation of each block, we decouple the whole training process into two stages: progressive model shrinking and progressive model growing.
no code implementations • 9 Apr 2024 • ZhiHao Lin, Wei Ma, Tao Lin, Yaowen Zheng, Jingquan Ge, Jun Wang, Jacques Klein, Tegawende Bissyande, Yang Liu, Li Li
We introduce a governance framework centered on federated learning (FL), designed to foster the joint development and maintenance of open-source AI code models while safeguarding data privacy and security.
no code implementations • 18 Mar 2024 • Zhuoyuan Li, Zikun Yuan, Li Li, Dong Liu, Xiaohu Tang, Feng Wu
Moreover, the segmentation mask is considered in the joint rate-distortion optimization for motion estimation and partition estimation to derive the motion vector of different regions and partition more accurately.
no code implementations • 18 Mar 2024 • Zhiyang Guo, Wengang Zhou, Li Li, Min Wang, Houqiang Li
To address the above problem, we propose a novel motion-aware enhancement framework for dynamic scene reconstruction, which mines useful motion cues from optical flow to improve different paradigms of dynamic 3DGS.
1 code implementation • 13 Mar 2024 • Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen
Through this gateway, users have the opportunity to submit their questions, testing the models on a personalized and potentially broader range of capabilities.
no code implementations • 9 Mar 2024 • Cunhui Dong, Haichuan Ma, Haotian Zhang, Changsheng Gao, Li Li, Dong Liu
Neural network-based image coding has been developing rapidly since its birth.
no code implementations • 6 Mar 2024 • Xiangquan Gui, Binxuan Zhang, Li Li, Yi Yang
To solve such problems, in this paper, we (1) propose DLP-GAN (Draw Modern Chinese Landscape Photos with Generative Adversarial Network), an unsupervised cross-domain image translation framework with a novel asymmetric cycle mapping, and (2) introduce a generator based on a dense-fusion module to match different translation directions.
no code implementations • 29 Feb 2024 • Hongyi Liu, Zirui Liu, Ruixiang Tang, Jiayi Yuan, Shaochen Zhong, Yu-Neng Chuang, Li Li, Rui Chen, Xia Hu
Our aim is to raise awareness of the potential risks under the emerging share-and-play scenario, so as to proactively prevent potential consequences caused by LoRA-as-an-Attack.
1 code implementation • CVPR 2024 • Xiaohan Lei, Min Wang, Wengang Zhou, Li Li, Houqiang Li
As a new embodied vision task, Instance ImageGoal Navigation (IIN) aims to navigate to a specified object depicted by a goal image in an unexplored environment.
1 code implementation • 8 Feb 2024 • Mingyi Zhou, Xiang Gao, Jing Wu, Kui Liu, Hailong Sun, Li Li
Our findings emphasize the need for developers to carefully consider their model deployment strategies, and use white-box methods to evaluate the vulnerability of on-device models.
no code implementations • 29 Jan 2024 • Xihua Sheng, Li Li, Dong Liu, Houqiang Li
With the SDD-based motion model and long short-term temporal contexts fusion, our proposed learned video codec can obtain more accurate inter prediction.
1 code implementation • 26 Jan 2024 • Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Li Li, Xin Ning
In this paper, we propose a novel approach called Prompt Learning for FSCIL (PL-FSCIL), which harnesses the power of prompts in conjunction with a pre-trained Vision Transformer (ViT) model to address the challenges of FSCIL effectively.
class-incremental learning
Few-Shot Class-Incremental Learning
+2
1 code implementation • 23 Jan 2024 • Dachong Li, Li Li, Zhuangzhuang Chen, Jianqiang Li
Experimental results show that our shift-wise operator significantly improves the accuracy of a regular CNN while markedly reducing computational requirements.
1 code implementation • 18 Jan 2024 • Zhensu Sun, Xiaoning Du, Fu Song, Shangwen Wang, Li Li
These findings motivate our exploration of dynamic inference in code completion and inspire us to enhance it with a decision-making mechanism that stops the generation of incorrect code.
no code implementations • 14 Jan 2024 • Weian Guo, Zecheng Kang, Dongyang Li, Lun Zhang, Li Li
Therefore, the deployment of RSUs is of utmost importance in ensuring the quality of communication services.
no code implementations • 28 Dec 2023 • Jiazhang Zheng, Lei LI, Qiuping Liao, Cheng Li, Li Li, Yangxing Liu
This paper proposes a lightweight network that outperforms existing state-of-the-art (SOTA) methods in low-light enhancement tasks while minimizing computation.
1 code implementation • CVPR 2024 • Li Li, Jiawei Peng, Huiyi Chen, Chongyang Gao, Xu Yang
Inspired by the success of Large Language Models in dealing with new tasks via In-Context Learning (ICL) in NLP, researchers have also developed Large Vision-Language Models (LVLMs) with ICL capabilities.
no code implementations • 1 Nov 2023 • Yonghui Wang, Wengang Zhou, Hao Feng, Li Li, Houqiang Li
To handle this issue, we consider removing the shadow in a coarse-to-fine fashion and propose a simple but effective Progressive Recurrent Network (PRNet).
1 code implementation • 27 Oct 2023 • Xinyu She, Yue Liu, Yanjie Zhao, Yiling He, Li Li, Chakkrit Tantithamthavorn, Zhan Qin, Haoyu Wang
After carefully examining these studies, we designed a taxonomy of pitfalls in LM4Code research and conducted a systematic study to summarize the issues, implications, current solutions, and challenges of different pitfalls for LM4Code systems.
no code implementations • 9 Oct 2023 • Li Li, You Qin, Wei Ji, Yuxiao Zhou, Roger Zimmermann
Panoptic Scene Graph Generation (PSG) involves the detection of objects and the prediction of their corresponding relationships (predicates).
no code implementations • 29 Sep 2023 • Wei Ji, Li Li, Hao Fei, Xiangyan Liu, Xun Yang, Juncheng Li, Roger Zimmermann
Referring Image Understanding (RIS) has been extensively studied over the past decade, leading to the development of advanced algorithms.
no code implementations • 29 Sep 2023 • Haotian Zhang, Li Li, Dong Liu
In principle, we find two factors crucial: one is the discrepancy between the surrogate and rounding, leading to train-test mismatch; the other is gradient estimation risk due to the surrogate, which consists of bias and variance of the gradient estimation.
1 code implementation • 25 Sep 2023 • Li Li, Feng Li, Yanfei Kang
In economics and many other forecasting domains, the real world problems are too complex for a single model that assumes a specific data generation process.
no code implementations • 14 Sep 2023 • Terry Yue Zhuo, Xiaoning Du, Zhenchang Xing, Jiamou Sun, Haowei Quan, Li Li, Liming Zhu
The correctness and unambiguity of API usage among these code models are crucial for achieving desirable program functionalities, requiring them to learn various API fully qualified names structurally and semantically.
1 code implementation • 7 Sep 2023 • Li Li, Qingqing Li, Guozheng Xu, Pengwei Zhou, Jingmin Tu, Jie Li, Mingming Li, Jian Yao
To solve this problem, we propose a boundary-aware point clustering approach in Euclidean and embedding spaces constructed by a multi-task deep network for roof plane segmentation.
1 code implementation • 28 Aug 2023 • Zhensu Sun, Xiaoning Du, Fu Song, Li Li
Even worse, the ``black-box'' nature of neural models sets a high barrier for externals to audit their training datasets, which further connives these unauthorized usages.
no code implementations • 25 Aug 2023 • Jacob Wiebe, Ranwa Al Mallah, Li Li
Recent advancements in deep learning techniques have opened new possibilities for designing solutions for autonomous cyber defence.
1 code implementation • 21 Aug 2023 • Xinyi Hou, Yanjie Zhao, Yue Liu, Zhou Yang, Kailong Wang, Li Li, Xiapu Luo, David Lo, John Grundy, Haoyu Wang
Nevertheless, a comprehensive understanding of the application, effects, and possible limitations of LLMs on SE is still in its early stages.
1 code implementation • 18 Aug 2023 • Chenwei Wang, You Qin, Li Li, Siyi Luo, Yulin Huang, Jifang Pei, Yin Zhang, Jianyu Yang
As a result, it has a detrimental causal effect damaging the efficacy of feature $X$ extracted from SAR images, leading to weak generalization of SAR ATR with limited data.
no code implementations • ICCV 2023 • Hao Feng, Wendi Wang, Jiajun Deng, Wengang Zhou, Li Li, Houqiang Li
To make the best of such rectification cues, we introduce SimFIR, a simple framework for fisheye image rectification based on self-supervised representation learning.
1 code implementation • ICCV 2023 • Yufei Yin, Jiajun Deng, Wengang Zhou, Li Li, Houqiang Li
These inaccurate high-scoring region proposals will mislead the training of subsequent refinement modules and thus hamper the detection performance.
no code implementations • 10 Aug 2023 • Shaocong Liu, Tao Wang, Yan Zhang, Ruqin Zhou, Li Li, Chenguang Dai, Yongsheng Zhang, Longguang Wang, Hanyun Wang
The adjacent points with the same category labels are then clustered together using the Euclidean clustering algorithm to obtain the semantic instances, which are represented by three kinds of attributes including spatial location information, semantic categorical information, and global geometric shape information.
no code implementations • 8 Aug 2023 • Weichao Zhao, Hezhen Hu, Wengang Zhou, Li Li, Houqiang Li
Reconstructing interacting hands from monocular RGB data is a challenging task, as it involves many interfering factors, e. g. self- and mutual occlusion and similar textures.
1 code implementation • 7 Aug 2023 • Renjie Liang, Yiming Yang, Hui Lu, Li Li
To tackle this problem, we propose a novel efficient multi-teacher model (EMTM) based on knowledge distillation to transfer diverse knowledge from both heterogeneous and isomorphic networks.
1 code implementation • 28 Jul 2023 • Li Li, Wei Ji, Yiming Wu, Mengze Li, You Qin, Lina Wei, Roger Zimmermann
To promise consistency and accuracy during the transfer process, we propose to measure the invariance of representations in each predicate class, and learn unbiased prototypes of predicates with different intensities.
Ranked #3 on
Panoptic Scene Graph Generation
on PSG Dataset
1 code implementation • 22 Jul 2023 • Chen Rui, Liang Guotao, Ma Chenrui, Han Qilong, Li Li, Huang Xiao
In this paper, we systematically investigate various temporal information for sequential recommendation and identify three types of advantageous temporal patterns beyond order, including absolute time information, relative item time intervals and relative recommendation time intervals.
no code implementations • 13 Jul 2023 • Wei Hu, Xuhong Wang, Ding Wang, Shengyue Yao, Zuqiu Mao, Li Li, Fei-Yue Wang, Yilun Lin
In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other benefits.
no code implementations • 11 Jul 2023 • Chuanbo Tang, Xihua Sheng, Zhuoyuan Li, Haotian Zhang, Li Li, Dong Liu
In the offline stage, we fine-tune a trained optical flow estimation network with the motion information provided by a traditional (non-deep) video compression scheme, e. g. H. 266/VVC, as we believe the motion information of H. 266/VVC achieves a better rate-distortion trade-off.
no code implementations • 1 Jul 2023 • Shuzhe Chen, Li Li, Zhichao Lin, Ke Zhang, Ying Gong, Lu Wang, Xu Wu, Maokun Li, Yuanlin Song, Fan Yang, Shenheng Xu
A simple convolutional neural network is used for classification.
no code implementations • 19 Jun 2023 • Xihua Sheng, Li Li, Dong Liu, Houqiang Li
Such compact representations need to be decoded back to pixels before being displayed to humans and - as usual - before being enhanced/analyzed by machine vision algorithms.
no code implementations • 17 Jun 2023 • Shitian Li, Chunlin Tian, Kahou Tam, Rui Ma, Li Li
In this systematic survey, we aim to explore the current state-of-the-art techniques for breaking on-device training memory walls, focusing on methods that can enable larger and more complex models to be trained on resource-constrained devices.
no code implementations • 12 Jun 2023 • DianChao Lin, Li Li
Urban traffic network is such a system.
1 code implementation • 31 May 2023 • Terry Yue Zhuo, Zhou Yang, Zhensu Sun, YuFei Wang, Li Li, Xiaoning Du, Zhenchang Xing, David Lo
This paper fills this gap by conducting a comprehensive and integrative survey of data augmentation for source code, wherein we systematically compile and encapsulate existing literature to provide a comprehensive overview of the field.
no code implementations • 29 May 2023 • Lirui Xu, Pang Wu, Pan Xia, Fanglin Geng, Peng Wang, Xianxiang Chen, Zhenfeng Li, Lidong Du, Shuping Liu, Li Li, Hongbo Chang, Zhen Fang
In in vitro cardiovascular phantom experiments, the results demonstrated high accuracy in the measurement of PP (error < 3 mmHg) and blood pressure waveform (root-mean-square-errors (RMSE) < 2 mmHg, correlation coefficient (r) > textgreater 0. 99).
no code implementations • 29 May 2023 • DianChao Lin, Li Li
This paper proposes an efficient safety-oriented car-following model for CAVs considering the impact of discrete signals.
no code implementations • 27 May 2023 • Yangjie Zhou, Yaoxu Song, Jingwen Leng, Zihan Liu, Weihao Cui, Zhendong Zhang, Cong Guo, Quan Chen, Li Li, Minyi Guo
Graph neural networks (GNNs) are powerful tools for exploring and learning from graph structures and features.
1 code implementation • 25 May 2023 • Ding Wang, Xuhong Wang, Liang Chen, Shengyue Yao, Ming Jing, Honghai Li, Li Li, Shiqiang Bao, Fei-Yue Wang, Yilun Lin
To the best of our knowledge, this is the first traffic simulator that can automatically learn traffic patterns from real-world data and efficiently generate accurate and realistic traffic environments.
no code implementations • 24 May 2023 • Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
However, model editing for graph neural networks (GNNs) is rarely explored, despite GNNs' widespread applicability.
no code implementations • 20 May 2023 • Wei Ma, Shangqing Liu, ZhiHao Lin, Wenhan Wang, Qiang Hu, Ye Liu, Cen Zhang, Liming Nie, Li Li, Yang Liu
We break down the abilities needed for artificial intelligence~(AI) models to address SE tasks related to code analysis into three categories: 1) syntax understanding, 2) static behavior understanding, and 3) dynamic behavior understanding.
no code implementations • 12 May 2023 • Long Chen, Yuchen Li, Chao Huang, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions.
1 code implementation • NeurIPS 2023 • Ao Zhang, Hao Fei, Yuan YAO, Wei Ji, Li Li, Zhiyuan Liu, Tat-Seng Chua
While developing a new multimodal LLM (MLLM) by pre-training on tremendous image-text pairs from scratch can be exceedingly resource-consuming, connecting an existing LLM with a comparatively lightweight visual prompt generator (VPG) becomes a feasible paradigm.
no code implementations • 3 Apr 2023 • Li Li, Jean-Pierre S. El Rami, Adrian Taylor, James Hailing Rao, Thomas Kunz
This work aims to enable autonomous agents for network cyber operations (CyOps) by applying reinforcement and deep reinforcement learning (RL/DRL).
no code implementations • 3 Apr 2023 • Li Li, Jean-Pierre S. El Rami, Adrian Taylor, James Hailing Rao, Thomas Kunz
This work presents a systematic solution to automatically generate a high-fidelity simulator in the Cyber Gym for Intelligent Learning (CyGIL).
no code implementations • 3 Apr 2023 • Thomas Kunz, Christian Fisher, James La Novara-Gsell, Christopher Nguyen, Li Li
In particular, training a blue agent jointly with a red agent increases the blue agent's capability to thwart sophisticated red agents.
no code implementations • 30 Mar 2023 • Long Chen, Yuchen Li, Chao Huang, Bai Li, Yang Xing, Daxin Tian, Li Li, Zhongxu Hu, Xiaoxiang Na, Zixuan Li, Siyu Teng, Chen Lv, Jinjun Wang, Dongpu Cao, Nanning Zheng, Fei-Yue Wang
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits.
no code implementations • CVPR 2023 • Zhiyang Guo, Wengang Zhou, Min Wang, Li Li, Houqiang Li
We propose a novel framework to reconstruct accurate appearance and geometry with neural radiance fields (NeRF) for interacting hands, enabling the rendering of photo-realistic images and videos for gesture animation from arbitrary views.
1 code implementation • CVPR 2023 • Li Li, Hubert P. H. Shum, Toby P. Breckon
Whilst the availability of 3D LiDAR point cloud data has significantly grown in recent years, annotation remains expensive and time-consuming, leading to a demand for semi-supervised semantic segmentation methods with application domains such as autonomous driving.
Ranked #1 on
3D Semantic Segmentation
on ScribbleKITTI
(mIoU-1% metric)
no code implementations • 18 Feb 2023 • Hao Li, Li Li, Yunmeng Huang, Ning li, Yongtao Zhang
Few-shot learning (FSL) requires a model to classify new samples after learning from only a few samples.
1 code implementation • 12 Feb 2023 • Chi Zhang, Rui Chen, Xiangyu Zhao, Qilong Han, Li Li
In practical recommendation scenarios, users often interact with items under multi-typed behaviors (e. g., click, add-to-cart, and purchase).
no code implementations • 10 Jan 2023 • Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Tirthankar Roy, Chonggang Xu, Binayak Mohanty, Kathryn Lawson
Here we present differentiable geoscientific modeling as a powerful pathway toward dissolving the perceived barrier between them and ushering in a paradigm shift.
1 code implementation • ICCV 2023 • Shengxi Li, Jialu Zhang, Yifei Li, Mai Xu, Xin Deng, Li Li
The emergence of conditional generative adversarial networks (cGANs) has revolutionised the way we approach and control the generation, by means of adversarially learning joint distributions of data and auxiliary information.
1 code implementation • 23 Dec 2022 • Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
To bridge the gap, we introduce a Personalized Subgraph Selector (PS2) as a plug-and-play framework to automatically, personally, and inductively identify optimal subgraphs for different edges when performing GNNLP.
no code implementations • 28 Nov 2022 • YiXuan Wang, Wengang Zhou, Jianmin Bao, Weilun Wang, Li Li, Houqiang Li
The key idea of our CLIP2GAN is to bridge the output feature embedding space of CLIP and the input latent space of StyleGAN, which is realized by introducing a mapping network.
no code implementations • 10 Nov 2022 • Jiawei Zhang, Shen Li, Li Li
Connected and automated vehicles (CAVs) are viewed as a special kind of robots that have the potential to significantly improve the safety and efficiency of traffic.
no code implementations • 3 Nov 2022 • Li Li, Dongxing Xu, Haoran Wei, Yanhua Long
Exploiting effective target modeling units is very important and has always been a concern in end-to-end automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
no code implementations • 11 Oct 2022 • Yuxi Xiao, Li Li, Xiaodi Li, Jian Yao
In addition, in order to increase the robustness of our framework, we formulate the likelihood function of the correlations of 2D image matches as a Gaussian and Uniform mixture distribution which takes the uncertainty caused by illumination changes, image noise and moving objects into account.
1 code implementation • 13 Sep 2022 • Zhensu Sun, Xiaoning Du, Fu Song, Shangwen Wang, Mingze Ni, Li Li, David Lo
To fill this significant gap, we first investigate the prompts of unhelpful code completions, called "low-return prompts".
no code implementations • 12 Sep 2022 • Qianqian Ma, Li Li, Junhui Shen, Haowei Guan, Guangcheng Ma, Hongwei Xia
This paper investigates the fuzzy $H_{\infty}$ filter design issue for nonlinear systems with time-varying delay.
no code implementations • 12 Sep 2022 • Qianqian Ma, Hongwei Xia, Li Li, Guangcheng Ma
This paper is concerned with the fuzzy $H_{\infty}$ filter design issue for nonlinear systems with time-varying delay.
no code implementations • 18 Aug 2022 • Hong Ren, Zhenkun Zhang, Zhangjie Peng, Li Li, Cunhua Pan
Then, we investigate the general scenario in which the RF signals are radiated during the flight, aiming to minimize the total energy consumption of the UAV by jointly optimizing the UAV's trajectory, flight time and the RIS's reflection coefficients.
no code implementations • 12 Jul 2022 • Shuai Huo, Dong Liu, Li Li, Siwei Ma, Feng Wu, Wen Gao
Our idea is to provide multiple discrete starting points in the global space and optimize the local optimum around each point by numerical algorithm efficiently.
no code implementations • 18 Jun 2022 • Qinghua Tao, Li Li, Xiaolin Huang, Xiangming Xi, Shuning Wang, Johan A. K. Suykens
To apply PWLNN methods, both the representation and the learning have long been studied.
no code implementations • Findings (NAACL) 2022 • Xin Wang, Yasheng Wang, Yao Wan, Jiawei Wang, Pingyi Zhou, Li Li, Hao Wu, Jin Liu
Specifically, we first extract multiple code views using compiler tools, and learn the complementary information among them under a contrastive learning framework.
no code implementations • 21 Apr 2022 • Jiaqi Xue, Chentian Ma, Li Li, Xuan Wen
Melanoma is the most malignant skin tumor and usually cancerates from normal moles, which is difficult to distinguish benign from malignant in the early stage.
1 code implementation • 15 Apr 2022 • Yang Xu, Li Li, Haiyang Xu, Songfang Huang, Fei Huang, Jianfei Cai
This drawback inspires the researchers to develop a homogeneous architecture that facilitates end-to-end training, for which Transformer is the perfect one that has proven its huge potential in both vision and language domains and thus can be used as the basic component of the visual encoder and language decoder in an IC pipeline.
1 code implementation • CVPR 2022 • Liang Gao, Huazhu Fu, Li Li, YingWen Chen, Ming Xu, Cheng-Zhong Xu
Federated learning (FL) allows multiple clients to collectively train a high-performance global model without sharing their private data.
no code implementations • 11 Mar 2022 • Dongmei Xue, Haichuan Ma, Li Li, Dong Liu, Zhiwei Xiong
Volumetric image compression has become an urgent task to effectively transmit and store images produced in biological research and clinical practice.
1 code implementation • 3 Mar 2022 • He Ma, Arunachalam Narayanaswamy, Patrick Riley, Li Li
Systematic development of accurate density functionals has been a decades-long challenge for scientists.
1 code implementation • 14 Feb 2022 • Zhensu Sun, Yan Liu, Xiaoning Du, Li Li
The performance of neural code search is significantly influenced by the quality of the training data from which the neural models are derived.
1 code implementation • IEEE Transactions on Intelligent Transportation Systems 2022 • Bai Li, Yakun Ouyang, Li Li, Youmin Zhang
This paper is focused on the trajectory planning task for autonomous driving on a curvy road.
no code implementations • NeurIPS 2021 • Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
In this paper, we propose a framework that unifies sequence- and graph-based methods as energy-based models (EBMs) with different energy functions.
no code implementations • 1 Dec 2021 • Xihua Sheng, Li Li, Dong Liu, Zhiwei Xiong
In this paper, we propose a Multi-Scale Graph Attention Network (MS-GAT) to remove the artifacts of point cloud attributes compressed by G-PCC.
1 code implementation • 27 Nov 2021 • Xihua Sheng, Jiahao Li, Bin Li, Li Li, Dong Liu, Yan Lu
From the stored propagated features, we propose to learn multi-scale temporal contexts, and re-fill the learned temporal contexts into the modules of our compression scheme, including the contextual encoder-decoder, the frame generator, and the temporal context encoder.
no code implementations • 25 Nov 2021 • Xiaoxiao Zhao, Jinlong Lei, Li Li, Jie Chen
This paper studies a distributed policy gradient in collaborative multi-agent reinforcement learning (MARL), where agents over a communication network aim to find the optimal policy to maximize the average of all agents' local returns.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
no code implementations • 30 Oct 2021 • Miao Zhang, Miaojing Shi, Li Li
Last, to enhance the embedding space learning, an additional pixel-wise metric learning module is introduced with triplet loss formulated on the pixel-level embedding of the input image.
no code implementations • 28 Oct 2021 • Bhupalee Kalita, Ryan Pederson, Jielun Chen, Li Li, Kieron Burke
Kohn-Sham regularizer (KSR) is a differentiable machine learning approach to finding the exchange-correlation functional in Kohn-Sham density functional theory (DFT) that works for strongly correlated systems.
1 code implementation • 25 Oct 2021 • Zhensu Sun, Xiaoning Du, Fu Song, Mingze Ni, Li Li
Github Copilot, trained on billions of lines of public code, has recently become the buzzword in the computer science research and practice community.
no code implementations • 30 Sep 2021 • Haichuan Ma, Dong Liu, Cunhui Dong, Li Li, Feng Wu
However, this nature was seldom considered in previous studies on image compression, which usually chose one possible image as reconstruction, e. g. the one with the maximal a posteriori probability.
no code implementations • ICLR 2022 • Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
Instance-dependent label noise (IDN) widely exists in real-world datasets and usually misleads the training of deep neural networks.
no code implementations • ICLR 2022 • Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu
Based on the implementation, we propose a memory-efficient framework called ``EXACT'', which for the first time demonstrate the potential and evaluate the feasibility of training GNNs with compressed activations.
no code implementations • 29 Sep 2021 • Dongping Liao, Xitong Gao, Yiren Zhao, Hao Dai, Li Li, Kafeng Wang, Kejiang Ye, Yang Wang, Cheng-Zhong Xu
Federated learning (FL) enables edge clients to train collaboratively while preserving individual's data privacy.
no code implementations • 18 Sep 2021 • Dongmei Xue, Haichuan Ma, Li Li, Dong Liu, Zhiwei Xiong
With the rapid development of whole brain imaging technology, a large number of brain images have been produced, which puts forward a great demand for efficient brain image compression methods.
no code implementations • 7 Sep 2021 • Li Li, Raed Fayad, Adrian Taylor
Given the success of reinforcement learning (RL) in various domains, it is promising to explore the application of its methods to the development of intelligent and autonomous cyber agents.
no code implementations • 4 Sep 2021 • Xiuxian Li, Kuo-Yi Lin, Li Li, Yiguang Hong, Jie Chen
For the first two cases, it can be shown that the scaled signGD converges at a linear rate.
no code implementations • 30 Aug 2021 • Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
Graph neural networks (GNNs), which learn the node representations by recursively aggregating information from its neighbors, have become a predominant computational tool in many domains.
no code implementations • 10 Aug 2021 • Xin Wang, Yasheng Wang, Fei Mi, Pingyi Zhou, Yao Wan, Xiao Liu, Li Li, Hao Wu, Jin Liu, Xin Jiang
Code representation learning, which aims to encode the semantics of source code into distributed vectors, plays an important role in recent deep-learning-based models for code intelligence.
no code implementations • 4 Aug 2021 • Li Li, Yanfei Kang, Feng Li
In this work, we propose a novel framework for density forecast combination by constructing time-varying weights based on time series features, which is called Feature-based Bayesian Forecasting Model Averaging (FEBAMA).
no code implementations • ACL 2021 • Qiuxiang He, Guoping Huang, Qu Cui, Li Li, Lemao Liu
It is generally believed that a translation memory (TM) should be beneficial for machine translation tasks.
1 code implementation • NeurIPS 2021 • Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
To this end, we analyze the bottleneck of deep GNNs by leveraging the Dirichlet energy of node embeddings, and propose a generalizable principle to guide the training of deep GNNs.
1 code implementation • 24 Jun 2021 • Kahou Tam, Li Li, Bo Han, Chengzhong Xu, Huazhu Fu
Federated learning (FL) collaboratively trains a shared global model depending on multiple local clients, while keeping the training data decentralized in order to preserve data privacy.
no code implementations • 26 May 2021 • Xinran Li, Kuo-Yi Lin, Min Meng, Xiuxian Li, Li Li, Yiguang Hong, Jie Chen
Due to the growing awareness of driving safety and the development of sophisticated technologies, advanced driving assistance system (ADAS) has been equipped in more and more vehicles with higher accuracy and lower price.
1 code implementation • 19 May 2021 • Wentao Ouyang, Xiuwu Zhang, Shukui Ren, Li Li, Kun Zhang, Jinmei Luo, Zhaojie Liu, Yanlong Du
For existing old ads, GMEs first build a graph to connect them with new ads, and then adaptively distill useful information.
no code implementations • 15 May 2021 • Xinyu Peng, Jiawei Zhang, Fei-Yue Wang, Li Li
As a promising tool to better understand the learning dynamic of minibatch SGD, the information bottleneck (IB) theory claims that the optimization process consists of an initial fitting phase and the following compression phase.
no code implementations • 11 May 2021 • Huihuang Chen, Li Li, Jie Chen, Kuo-Yi Lin
In addition to aligning the global distribution, the real domain adaptation should also align the meso distribution and the micro distribution.
no code implementations • 22 Apr 2021 • Jing Wu, Mingyi Zhou, Ce Zhu, Yipeng Liu, Mehrtash Harandi, Li Li
Recently, adversarial attack methods have been developed to challenge the robustness of machine learning models.
no code implementations • 21 Apr 2021 • Huaxin Pei, Yi Zhang, Qinghua Tao, Shuo Feng, Li Li
Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years.
no code implementations • 16 Apr 2021 • Yu Zhang, Moming Duan, Duo Liu, Li Li, Ao Ren, Xianzhang Chen, Yujuan Tan, Chengliang Wang
Asynchronous FL has a natural advantage in mitigating the straggler effect, but there are threats of model quality degradation and server crash.
no code implementations • 15 Apr 2021 • Li Li, Moming Duan, Duo Liu, Yu Zhang, Ao Ren, Xianzhang Chen, Yujuan Tan, Chengliang Wang
In our framework, the server evaluates devices' value of training based on their training loss.
no code implementations • 7 Apr 2021 • Vivek Singh Bawa, Gurkirt Singh, Francis KapingA, Inna Skarga-Bandurova, Elettra Oleari, Alice Leporini, Carmela Landolfo, Pengfei Zhao, Xi Xiang, Gongning Luo, Kuanquan Wang, Liangzhi Li, Bowen Wang, Shang Zhao, Li Li, Armando Stabile, Francesco Setti, Riccardo Muradore, Fabio Cuzzolin
For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging.
no code implementations • 11 Mar 2021 • Chi Zhang, Zihang Lin, Liheng Xu, Zongliang Li, Wei Tang, Yuehu Liu, Gaofeng Meng, Le Wang, Li Li
The key procedure of haze image translation through adversarial training lies in the disentanglement between the feature only involved in haze synthesis, i. e. style feature, and the feature representing the invariant semantic content, i. e. content feature.
1 code implementation • 9 Mar 2021 • Yue Liu, Chakkrit Tantithamthavorn, Li Li, Yepang Liu
In this paper, we conducted a systematic literature review to search and analyze how deep learning approaches have been applied in the context of malware defenses in the Android environment.
1 code implementation • 4 Mar 2021 • Jiawei Wang, Li Li, Andreas Zeller
More than ninety percent of published Jupyter notebooks do not state dependencies on external packages.
Software Engineering
no code implementations • 23 Feb 2021 • Li-Zheng Liu, Yu-Zhe Zhang, Zheng-Da Li, Rui Zhang, Xu-Fei Yin, Yue-Yang Fei, Li Li, Nai-Le Liu, Feihu Xu, Yu-Ao Chen, Jian-Wei Pan
Distributed quantum metrology can enhance the sensitivity for sensing spatially distributed parameters beyond the classical limits.
Quantum Physics
no code implementations • 5 Feb 2021 • Wenting Zou, Li Li, Zichen Xu, Chengzhong Xu
To address the conflict between learning SLO and energy efficiency, we propose DEAL, an energy efficient learning system that saves energy and preserves privacy with a decremental learning design.
no code implementations • 17 Jan 2021 • YingJie Xu, Kai Yu, Li Li, Xianfu Lei, Li Hao, Cheng-Xiang Wang
As a potential development direction of future transportation, the vacuum tube ultra-high-speed train (UHST) wireless communication systems have newly different channel characteristics from existing high-speed train (HST) scenarios.
no code implementations • 4 Dec 2020 • Yanan Wang, Yong Ge, Li Li, Rui Chen, Tong Xu
To improve adaptation efficiency, we learn to recover the user policy and reward from only a few interactions via an inverse reinforcement learning method to assist a meta-level recommendation agent.
Model-based Reinforcement Learning
Recommendation Systems
+3
1 code implementation • 22 Oct 2020 • Murphy Yuezhen Niu, Andrew M. Dai, Li Li, Augustus Odena, Zhengli Zhao, Vadim Smelyanskyi, Hartmut Neven, Sergio Boixo
Given a quantum circuit, a quantum computer can sample the output distribution exponentially faster in the number of bits than classical computers.
1 code implementation • 17 Sep 2020 • Li Li, Stephan Hoyer, Ryan Pederson, Ruoxi Sun, Ekin D. Cubuk, Patrick Riley, Kieron Burke
Including prior knowledge is important for effective machine learning models in physics, and is usually achieved by explicitly adding loss terms or constraints on model architectures.
no code implementations • 21 Aug 2020 • Ninghao Liu, Yong Ge, Li Li, Xia Hu, Rui Chen, Soo-Hyun Choi
Different from previous work, in our model, factor discovery and representation learning are simultaneously conducted, and we are able to handle extra attribute information and knowledge.
no code implementations • 12 Aug 2020 • Wenqing Liu, Miaojing Shi, Teddy Furon, Li Li
This paper presents a DNN bottleneck reinforcement scheme to alleviate the vulnerability of Deep Neural Networks (DNN) against adversarial attacks.
no code implementations • 14 Jul 2020 • Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
Retrosynthesis -- the process of identifying a set of reactants to synthesize a target molecule -- is of vital importance to material design and drug discovery.
Ranked #5 on
Single-step retrosynthesis
on USPTO-50k
no code implementations • ECCV 2020 • Zhen Zhao, Miaojing Shi, Xiaoxiao Zhao, Li Li
To learn a reliable people counter from crowd images, head center annotations are normally required.
2 code implementations • ICLR 2021 • Subham Sekhar Sahoo, Subhashini Venugopalan, Li Li, Rishabh Singh, Patrick Riley
In this work, we propose a technique for combining gradient-based methods with symbolic techniques to scale such analyses and demonstrate its application for model explanation.
no code implementations • 28 Jun 2020 • Li Li, Theodoros Pantelidis, Joseph Y. J. Chow, Saif Eddin Jabari
To overcome this complexity, we employ an online minimum drift plus penalty (MDPP) approach for SAEV systems that (i) does not require a priori knowledge of customer arrival rates to the different parts of the system (i. e. it is practical from a real-world deployment perspective), (ii) ensures the stability of customer waiting times, (iii) ensures that the deviation of dispatch costs from a desirable dispatch cost can be controlled, and (iv) has a computational time-complexity that allows for real-time implementation.
no code implementations • 25 Jun 2020 • Yuzhu Guo, Kang Pan, Simeng Li, Zongchang Han, Kexin Wang, Li Li
Autoencoders have been widely used for dimensional reduction and feature extraction.
no code implementations • 9 Jun 2020 • Zhangjie Peng, Zhenkun Zhang, Cunhua Pan, Li Li, A. Lee Swindlehurst
Low-cost passive intelligent reflecting surfaces (IRSs) have recently been envisioned as a revolutionary technology capable of reconfiguring the wireless propagation environment through carefully tuning reflection elements.
1 code implementation • 31 May 2020 • Hong Yu, Li Li, Hsin-hui Huang, Yang Wang, Yingtong Liu, Edison Ong, Anthony Huffman, Tao Zeng, Jingsong Zhang, Pengpai Li, Zhiping Liu, Xiangyan Zhang, Xianwei Ye, Samuel K. Handelman, Gerry Higgins, Gilbert S. Omenn, Brian Athey, Junguk Hur, Luonan Chen, Yongqun He
We hypothesized that ontology can be used as an integrative platform to classify and analyze HCI and disease outcomes.
Other Quantitative Biology
1 code implementation • 27 May 2020 • Daniel Liang, Li Li, Stefan Leichenauer
The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.
Quantum Physics
no code implementations • 26 May 2020 • Cong Wang, Yanru Xiao, Xing Gao, Li Li, Jun Wang
We show the feasibility of training with mobile CPUs, where training 100 epochs takes less than 10 mins and can be boosted 3-5 times with feature transfer.
no code implementations • 22 Apr 2020 • Yijun Quan, Chang-Tsun Li, Yujue Zhou, Li Li
Device fingerprints like sensor pattern noise (SPN) are widely used for provenance analysis and image authentication.
no code implementations • 17 Apr 2020 • Senlin Shu, Fengmao Lv, Yan Yan, Li Li, Shuo He, Jun He
In this article, we propose to leverage the data augmentation technique to improve the performance of multi-label learning.
no code implementations • 6 Apr 2020 • Kai Chen, Jian Yao, Jingmin Tu, Yahui Liu, Yinxuan Li, Li Li
Recently, works on improving the naturalness of stitching images gain more and more extensive attention.
no code implementations • 27 Jan 2020 • Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen
With the explosive growth of online products and content, recommendation techniques have been considered as an effective tool to overcome information overload, improve user experience, and boost business revenue.
no code implementations • 13 Jan 2020 • Harrison Ball, Michael J. Biercuk, Andre Carvalho, Jiayin Chen, Michael Hush, Leonardo A. De Castro, Li Li, Per J. Liebermann, Harry J. Slatyer, Claire Edmunds, Virginia Frey, Cornelius Hempel, Alistair Milne
Manipulating quantum computing hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers.
Quantum Physics