no code implementations • ACL 2022 • Ying Li, Shuaike Li, Min Zhang
To address this issue, we for the first time apply a dynamic matching network on the shared-private model for semi-supervised cross-domain dependency parsing.
1 code implementation • COLING 2022 • Sixing Wu, Ying Li, Ping Xue, Dawei Zhang, Zhonghai Wu
However, a dialogue is always aligned to a lot of retrieved fact candidates; as a result, the linearized text is always lengthy and then significantly increases the burden of using PLMs.
no code implementations • Findings (EMNLP) 2021 • Ying Li, Meishan Zhang, Zhenghua Li, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan
Thanks to the strong representation learning capability of deep learning, especially pre-training techniques with language model loss, dependency parsing has achieved great performance boost in the in-domain scenario with abundant labeled training data for target domains.
1 code implementation • EMNLP 2021 • Sixing Wu, Ying Li, Minghui Wang, Dawei Zhang, Yang Zhou, Zhonghai Wu
Despite achieving remarkable performance, previous knowledge-enhanced works usually only use a single-source homogeneous knowledge base of limited knowledge coverage.
no code implementations • Findings (ACL) 2022 • Sixing Wu, Ying Li, Dawei Zhang, Zhonghai Wu
Knowledge-enhanced methods have bridged the gap between human beings and machines in generating dialogue responses.
no code implementations • 2 May 2024 • Shihao Wang, Zhiding Yu, Xiaohui Jiang, Shiyi Lan, Min Shi, Nadine Chang, Jan Kautz, Ying Li, Jose M. Alvarez
We further propose OmniDrive-nuScenes, a new visual question-answering dataset challenging the true 3D situational awareness of a model with comprehensive visual question-answering (VQA) tasks, including scene description, traffic regulation, 3D grounding, counterfactual reasoning, decision making and planning.
no code implementations • 2 Apr 2024 • Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang
Gaussian process latent variable models (GPLVMs) are a versatile family of unsupervised learning models, commonly used for dimensionality reduction.
no code implementations • 25 Mar 2024 • Qingping Zheng, Ling Zheng, Yuanfan Guo, Ying Li, Songcen Xu, Jiankang Deng, Hang Xu
Following this, the Reality Guidance Refinement (RGR) process refines artifacts by integrating this mask with realistic latent representations, improving alignment with the original image.
no code implementations • 18 Mar 2024 • Weiran Chen, Xin Li, Jiaqi Su, Guiqian Zhu, Ying Li, Yi Ji, Chunping Liu
As a cross-modal task, visual storytelling aims to generate a story for an ordered image sequence automatically.
no code implementations • 1 Mar 2024 • Yuqi Chen, Sixuan Li, Ying Li, Mohammad Atari
In this work, we develop a pipeline for historical-psychological text analysis in classical Chinese.
no code implementations • 25 Feb 2024 • Tianyu Chen, Haoyi Zhou, Ying Li, Hao Wang, Chonghan Gao, Shanghang Zhang, JianXin Li
Foundation models have revolutionized knowledge acquisition across domains, and our study introduces OmniArch, a paradigm-shifting approach designed for building foundation models in multi-physics scientific computing.
1 code implementation • 6 Feb 2024 • Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi
Pretrained large language models (LLMs) exhibit exceptional general language processing capabilities but come with significant demands on memory and computational resources.
no code implementations • 4 Dec 2023 • Yingli Yang, Zongkang Zhang, Anbang Wang, Xiaosi Xu, Xiaoting Wang, Ying Li
This random-circuit approach presents a trade-off between the expressive power of the variational wavefunction and time cost, in terms of the sampling cost of quantum circuits.
no code implementations • 14 Nov 2023 • Ying Li, Zhencai Zhu, Xiaoqiang Li, Chunyu Yang, Hao Lu
In this paper, we present how to apply RL to the autonomous control of mining electric locomotives.
1 code implementation • 7 Oct 2023 • Jie Hou, Zhiying Ma, Shihui Ying, Ying Li
However, we have discovered that neural network solvers based on L1 interpolation approximation are unable to fully exploit the benefits of neural networks, and the accuracy of these models is constrained to interpolation errors.
no code implementations • 7 Oct 2023 • Zhiying Ma, Jie Hou, Wenhao Zhu, Yaxin Peng, Ying Li
It establishes a temporal iteration scheme based on physical model-driven neural networks which effectively combines deep neural networks (DNNs) with interpolation approximation of fractional derivatives.
1 code implementation • 22 Sep 2023 • Xizhe Xue, Haokui Zhang, Ying Li, Liuwei Wan, Zongwen Bai, Mike Zheng Shou
In this paper, aiming to solve this problem, we propose the single-direction tuning (SDT) strategy, which serves as a bridge, allowing us to leverage existing labeled HSI datasets even RGB datasets to enhance the performance on new HSI datasets with limited samples.
no code implementations • 5 Sep 2023 • Wei Huang, Haotong Qin, Yangdong Liu, Jingzhuo Liang, Yulun Zhang, Ying Li, Xianglong Liu
Mixed-precision quantization leverages multiple bit-width architectures to unleash the accuracy and efficiency potential of quantized models.
2 code implementations • 3 Sep 2023 • Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis
The Gaussian process state-space model (GPSSM) has attracted extensive attention for modeling complex nonlinear dynamical systems.
no code implementations • 31 Aug 2023 • Qingping Zheng, Yuanfan Guo, Jiankang Deng, Jianhua Han, Ying Li, Songcen Xu, Hang Xu
Stable diffusion, a generative model used in text-to-image synthesis, frequently encounters resolution-induced composition problems when generating images of varying sizes.
1 code implementation • 11 Jul 2023 • Shukai Liu, Chenming Wu, Ying Li, Liangjun Zhang
This paper presents a new method that uses scores provided by humans instead of pairwise preferences to improve the feedback efficiency of interactive reinforcement learning.
no code implementations • 21 Jun 2023 • Chanyue Wu, Dong Wang, Hanyu Mao, Ying Li
Despite the proven significance of hyperspectral images (HSIs) in performing various computer vision tasks, its potential is adversely affected by the low-resolution (LR) property in the spatial domain, resulting from multiple physical factors.
no code implementations • 2 Jun 2023 • Ying Li, Xingwei Wang, Rongfei Zeng, Praveen Kumar Donta, Ilir Murturi, Min Huang, Schahram Dustdar
FDG combines the strengths of federated learning (FL) and domain generalization (DG) techniques to enable multiple source domains to collaboratively learn a model capable of directly generalizing to unseen domains while preserving data privacy.
3 code implementations • 18 Apr 2023 • Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen, Mingyu Xu, Kexin Wang, Ke Xu, Yu He, Ying Li, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, JianHua Tao
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
1 code implementation • ICCV 2023 • Shihao Wang, Yingfei Liu, Tiancai Wang, Ying Li, Xiangyu Zhang
On the standard nuScenes benchmark, it is the first online multi-view method that achieves comparable performance (67. 6% NDS & 65. 3% AMOTA) with lidar-based methods.
Ranked #1 on 3D Multi-Object Tracking on nuScenes Camera Only
no code implementations • 2 Feb 2023 • Bram van den Akker, Olivier Jeunen, Ying Li, Ben London, Zahra Nazari, Devesh Parekh
The research literature on these topics is broad and vast, but this can overwhelm practitioners, whose primary aim is to solve practical problems, and therefore need to decide on a specific instantiation or approach for each project.
no code implementations • ICCV 2023 • Chanyue Wu, Dong Wang, Yunpeng Bai, Hanyu Mao, Ying Li, Qiang Shen
Despite the proven significance of hyperspectral images (HSIs) in performing various computer vision tasks, its potential is adversely affected by the low-resolution (LR) property in the spatial domain, resulting from multiple physical factors.
no code implementations • 11 Dec 2022 • Shihao Wang, Xiaohui Jiang, Ying Li
The 3D-to-2D perspective inconsistency and global attention lead to a weak correlation between foreground tokens and queries, resulting in slow convergence.
1 code implementation • 11 Nov 2022 • Na lei, Zezeng Li, Zebin Xu, Ying Li, Xianfeng GU
This paper also underscores several promising future research directions and challenges in IMG.
no code implementations • 25 Oct 2022 • Zhaoji Zhang, Qinghua Guo, Ying Li, Ming Jin, Chongwen Huang
Furthermore, in conjunction with the AMP algorithm, a variational Bayesian inference based clustering (VBIC) algorithm is developed to solve this clustering problem.
no code implementations • 20 Oct 2022 • Yi Liu, Xuan Zhang, Ying Li, Guixin Liang, Yabing Jiang, Lixia Qiu, Haiping Tang, Fei Xie, Wei Yao, Yi Dai, Yu Qiao, Yali Wang
For this reason, we propose to advance research areas of video understanding, with a shift from traditional action recognition to industrial anomaly analysis.
no code implementations • 14 Sep 2022 • Ying Li, Djordje Tujkovic, Po-Han Huang
It is important that the wireless network is well optimized and planned, using the limited wireless spectrum resources, to serve the explosively growing traffic and diverse applications needs of end users.
1 code implementation • 18 Aug 2022 • Xizhe Xue, Dongdong Yu, Lingqiao Liu, Yu Liu, Satoshi Tsutsui, Ying Li, Zehuan Yuan, Ping Song, Mike Zheng Shou
Based on the single-stage instance segmentation framework, we propose a regularization model to predict foreground pixels and use its relation to instance segmentation to construct a cross-task consistency loss.
no code implementations • 31 Jul 2022 • Ying Li, Patrick Lambrix
The quality of ontologies in terms of their correctness and completeness is crucial for developing high-quality ontology-based applications.
no code implementations • Proceedings of the ACM Web Conference 2022 • Ying Li, Ye Tao, Su Zhang, Zhirong Hou, Zhonghai Wu
We train a model that integrates information from the user-item interaction graph and the user-user social graph and train two auxiliary models that only use one of the above graphs respectively.
no code implementations • 2 Apr 2022 • Kai Li, Ying Li, Lei Cheng, Qingjiang Shi, Zhi-Quan Luo
The downlink channel covariance matrix (CCM) acquisition is the key step for the practical performance of massive multiple-input and multiple-output (MIMO) systems, including beamforming, channel tracking, and user scheduling.
1 code implementation • CVPR 2022 • Qingping Zheng, Jiankang Deng, Zheng Zhu, Ying Li, Stefanos Zafeiriou
Specifically, DML-CSR designs a multi-task model which comprises face parsing, binary edge, and category edge detection.
Ranked #1 on Face Parsing on Helen
no code implementations • 25 Mar 2022 • Haiyang Sun, Zheng Lian, Bin Liu, Ying Li, Licai Sun, Cong Cai, JianHua Tao, Meng Wang, Yuan Cheng
Speech emotion recognition (SER) is an important research topic in human-computer interaction.
no code implementations • 19 Jan 2022 • Zinan Xiong, Chenxi Wang, Ying Li, Yan Luo, Yu Cao
We are interested in exploring its capability in human pose estimation, and thus propose a novel model based on transformer architecture, enhanced with a feature pyramid fusion structure.
1 code implementation • 21 Oct 2021 • Xizhe Xue, Haokui Zhang, Bei Fang, Zongwen Bai, Ying Li
Compared with search spaces proposed in previous works, the proposed hybrid search space is more aligned with the characteristic of HSI data, that is, HSIs have a relatively low spatial resolution and an extremely high spectral resolution.
no code implementations • 18 Jun 2021 • Wensheng Xia, Ying Li, Lan Zhang, Zhonghai Wu, Xiaoyong Yuan
To address these challenges, we propose a novel vertical federated learning framework named Cascade Vertical Federated Learning (CVFL) to fully utilize all horizontally partitioned labels to train neural networks with privacy-preservation.
no code implementations • 9 Apr 2021 • Prithwish Chakraborty, James Codella, Piyush Madan, Ying Li, Hu Huang, Yoonyoung Park, Chao Yan, Ziqi Zhang, Cheng Gao, Steve Nyemba, Xu Min, Sanjib Basak, Mohamed Ghalwash, Zach Shahn, Parthasararathy Suryanarayanan, Italo Buleje, Shannon Harrer, Sarah Miller, Amol Rajmane, Colin Walsh, Jonathan Wanderer, Gigi Yuen Reed, Kenney Ng, Daby Sow, Bradley A. Malin
Deep learning architectures have an extremely high-capacity for modeling complex data in a wide variety of domains.
no code implementations • 19 Mar 2021 • Xizhe Xue, Ying Li, Xiaoyue Yin, Qiang Shen
Discriminative correlation filters (DCF) and siamese networks have achieved promising performance on visual tracking tasks thanks to their superior computational efficiency and reliable similarity metric learning, respectively.
no code implementations • 4 Mar 2021 • Ying Li, Chi-Ho Cheung, Gang Xu
More importantly, the topological surface states in the LSM phase fill in the gap between the topological matters and silicon, which provide an opportunity to integrate the topological quantum devices and silicon chips together.
Materials Science
no code implementations • 16 Feb 2021 • Ying Li, Christos Argyropoulos
We demonstrate different ways to enhance a diverse range of quantum electrodynamic phenomena based on plasmonic configurations by using the classical dyadic tensor Green function formalism.
Quantization Optics
no code implementations • 8 Feb 2021 • Ying Li, Weipan Xu, Haohui Chen, Junhao Jiang, Xun Li
This study proposes a novel framework based on Mask R-CNN, named HTMask R-CNN, to extract new and old rural buildings even when the label is scarce.
1 code implementation • 12 Jan 2021 • Haokui Zhang, Chengrong Gong, Yunpeng Bai, Zongwen Bai, Ying Li
Correspondingly, different models need to be designed for different datasets, which further increases the workload of designing architectures; 2) the mainstream framework is a patch-to-pixel framework.
1 code implementation • 24 Dec 2020 • Haokui Zhang, Ying Li, Hao Chen, Chengrong Gong, Zongwen Bai, Chunhua Shen
For the inner search space, we propose a layer-wise architecture sharing strategy (LWAS), resulting in more flexible architectures and better performance.
2 code implementations • 7 Dec 2020 • Haokui Zhang, Ying Li, Yenan Jiang, Peng Wang, Qiang Shen, Chunhua Shen
In contrast to previous approaches, we do not impose restrictions over the source data sets, in which they do not have to be collected by the same sensors as the target data sets.
no code implementations • 5 Dec 2020 • Ze Wang, Sihao Ding, Ying Li, Jonas Fenn, Sohini Roychowdhury, Andreas Wallin, Lane Martin, Scott Ryvola, Guillermo Sapiro, Qiang Qiu
Point density varies significantly across such a long range, and different scanning patterns further diversify object representation in LiDAR.
no code implementations • COLING 2020 • Ying Li, Zhenghua Li, Min Zhang
The major challenge for current parsing research is to improve parsing performance on out-of-domain texts that are very different from the in-domain training data when there is only a small-scale out-domain labeled data.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Wenbin Jiang, Mengfei Guo, Yufeng Chen, Ying Li, Jinan Xu, Yajuan Lyu, Yong Zhu
This paper describes a novel multi-view classification model for knowledge graph completion, where multiple classification views are performed based on both content and context information for candidate triple evaluation.
no code implementations • 25 Nov 2020 • Xizhe Xue, Ying Li, Qiang Shen
Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Sixing Wu, Ying Li, Dawei Zhang, Zhonghai Wu
Given a query, our approach first retrieves a set of prototype dialogues that are relevant to the query.
no code implementations • 22 Oct 2020 • Kai Li, Ying Li, Lei Cheng, Qingjiang Shi, Zhi-Quan Luo
There is a fundamental trade-off between the channel representation resolution of codebooks and the overheads of feedback communications in the fifth generation new radio (5G NR) frequency division duplex (FDD) massive multiple-input and multiple-output (MIMO) systems.
no code implementations • 21 Oct 2020 • Weikai Tan, Dedong Zhang, Lingfei Ma, Ying Li, Lanying Wang, Jonathan Li
Stack interchanges are essential components of transportation systems.
no code implementations • 4 Aug 2020 • Yenan Jiang, Ying Li, Shanrong Zou, Haokui Zhang, Yunpeng Bai
However, the existing CNN-based models operate at the patch-level, in which pixel is separately classified into classes using a patch of images around it.
no code implementations • 24 Jul 2020 • Lingyi Liu, Yunpeng Bai, Ying Li
Ship detection has been an active and vital topic in the field of remote sensing for a decade, but it is still a challenging problem due to the large scale variations, the high aspect ratios, the intensive arrangement, and the background clutter disturbance.
no code implementations • 13 Jul 2020 • Huimei Han, Wenchao Zhai, Zhefu Wu, Ying Li, Jun Zhao, Mingda Chen
Simulation results show that, compared to the exiting random access scheme for the crowded asynchronous massive MIMO systems, the proposed scheme can improve the uplink throughput and estimate the effective timing offsets accurately at the same time.
no code implementations • 11 Jul 2020 • Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma, Hui Xiong
Then, we introduce a general route search algorithm coupled with an efficient station binding method for efficient route candidate generation.
1 code implementation • ACL 2020 • Sixing Wu, Ying Li, Dawei Zhang, Yang Zhou, Zhonghai Wu
We collect and build a large-scale Chinese dataset aligned with the commonsense knowledge for dialogue generation.
no code implementations • ACL 2020 • Jie Tan, Changlin Yang, Ying Li, Siliang Tang, Chen Huang, Yueting Zhuang
Measuring the scholarly impact of a document without citations is an important and challenging problem.
no code implementations • 20 May 2020 • Ying Li, Lingfei Ma, Zilong Zhong, Fei Liu, Dongpu Cao, Jonathan Li, Michael A. Chapman
In this paper, we provide a systematic review of existing compelling deep learning architectures applied in LiDAR point clouds, detailing for specific tasks in autonomous driving such as segmentation, detection, and classification.
1 code implementation • 15 May 2020 • Francesco Piccoli, Rajarathnam Balakrishnan, Maria Jesus Perez, Moraldeepsingh Sachdeo, Carlos Nunez, Matthew Tang, Kajsa Andreasson, Kalle Bjurek, Ria Dass Raj, Ebba Davidsson, Colin Eriksson, Victor Hagman, Jonas Sjoberg, Ying Li, L. Srikar Muppirisetty, Sohini Roychowdhury
Pedestrian intention recognition is very important to develop robust and safe autonomous driving (AD) and advanced driver assistance systems (ADAS) functionalities for urban driving.
no code implementations • 6 May 2020 • Jizhou Huang, Haifeng Wang, Haoyi Xiong, Miao Fan, An Zhuo, Ying Li, Dejing Dou
While these strategies have effectively dealt with the critical situations of outbreaks, the combination of the pandemic and mobility controls has slowed China's economic growth, resulting in the first quarterly decline of Gross Domestic Product (GDP) since GDP began to be calculated, in 1992.
no code implementations • 10 Apr 2020 • Yaodong Cui, Ren Chen, Wenbo Chu, Long Chen, Daxin Tian, Ying Li, Dongpu Cao
Autonomous vehicles were experiencing rapid development in the past few years.
1 code implementation • 18 Mar 2020 • Weikai Tan, Nannan Qin, Lingfei Ma, Ying Li, Jing Du, Guorong Cai, Ke Yang, Jonathan Li
Semantic segmentation of large-scale outdoor point clouds is essential for urban scene understanding in various applications, especially autonomous driving and urban high-definition (HD) mapping.
1 code implementation • 11 Feb 2020 • Haokui Zhang, Yu Liu, Bei Fang, Ying Li, Lingqiao Liu, Ian Reid
Hyperspectral image(HSI) classification has been improved with convolutional neural network(CNN) in very recent years.
no code implementations • 26 Sep 2019 • Ze Wang, Sihao Ding, Ying Li, Minming Zhao, Sohini Roychowdhury, Andreas Wallin, Guillermo Sapiro, Qiang Qiu
To the best of our knowledge, this paper is the first attempt to study cross-range LiDAR adaptation for object detection in point clouds.
1 code implementation • CVPR 2020 • Haokui Zhang, Ying Li, Hao Chen, Chunhua Shen
We also present analysis on the architectures found by NAS.
2 code implementations • ICCV 2019 • Haokui Zhang, Chunhua Shen, Ying Li, Yuanzhouhan Cao, Yu Liu, Youliang Yan
The temporal consistency loss is combined with the spatial loss to update the model in an end-to-end fashion.
Ranked #5 on Monocular Depth Estimation on Mid-Air Dataset
no code implementations • 4 Jul 2019 • Wenjun Liu, Yuchun Huang, Ying Li, Qi Chen
Specifically, we first propose the Multi-Dilation (MD) module, which can synthesize the crack features of multiple context sizes via dilated convolution with multiple rates.
no code implementations • 2 Feb 2019 • Yijiang Lian, Zhijie Chen, Jinlong Hu, Kefeng Zhang, Chunwei Yan, Muchenxuan Tong, Wenying Han, Hanju Guan, Ying Li, Ying Cao, Yang Yu, Zhigang Li, Xiaochun Liu, Yue Wang
In this paper, we present a generative retrieval method for sponsored search engine, which uses neural machine translation (NMT) to generate keywords directly from query.
no code implementations • 20 Dec 2018 • Xiao Yuan, Suguru Endo, Qi Zhao, Ying Li, Simon Benjamin
In this work, we introduce variational quantum simulation of mixed states under general stochastic evolution.
Quantum Physics
no code implementations • 20 Dec 2018 • Suguru Endo, Jinzhao Sun, Ying Li, Simon Benjamin, Xiao Yuan
Finally, we introduce variational quantum simulation for open system dynamics.
Quantum Physics
no code implementations • 24 Nov 2018 • Haokui Zhang, Ying Li, Peng Wang, Yu Liu, Chunhua Shen
Different from RGB videos, depth data in RGB-D videos provide key complementary information for tristimulus visual data which potentially could achieve accuracy improvement for action recognition.
no code implementations • COLING 2018 • Sixing Wu, Dawei Zhang, Ying Li, Xing Xie, Zhonghai Wu
Recent years have witnessed a surge of interest on response generation for neural conversation systems.
2 code implementations • 9 Apr 2018 • Sam McArdle, Tyson Jones, Suguru Endo, Ying Li, Simon Benjamin, Xiao Yuan
Imaginary time evolution is a powerful tool for studying quantum systems.
Quantum Physics
no code implementations • 19 Feb 2018 • Bin Liu, Ying Li, Soumya Ghosh, Zhaonan Sun, Kenney Ng, Jianying Hu
The proposed method is favorable for healthcare applications because in additional to improved prediction performance, relationships among the different risks and risk factors are also identified.
no code implementations • 11 Jan 2018 • Yuanhao Wang, Ying Li, Zhang-qi Yin, Bei Zeng
Entanglement is an important evidence that a quantum device can potentially solve problems intractable for classical computers.
Quantum Physics
1 code implementation • Remote Sensing 2017 • Ying Li, Haokui Zhang, Qiang Shen
Recent research has shown that using spectral–spatial information can considerably improve the performance of hyperspectral image (HSI) classification.
no code implementations • LREC 2012 • Ying Li, Yue Yu, Pascale Fung
Generally the existing monolingual corpora are not suitable for large vocabulary continuous speech recognition (LVCSR) of code-switching speech.