no code implementations • WMT (EMNLP) 2020 • Chi Hu, Hui Liu, Kai Feng, Chen Xu, Nuo Xu, Zefan Zhou, Shiqin Yan, Yingfeng Luo, Chenglong Wang, Xia Meng, Tong Xiao, Jingbo Zhu
This paper describes the submissions of the NiuTrans Team to the WMT 2020 Quality Estimation Shared Task.
no code implementations • EMNLP 2021 • Zongwei Liang, Junan Yang, Hui Liu, Keju Huang
experiments on the benchmark datasets show that the semantic filter based on relations can suppress the impact of other attribute dimensions and improve link prediction performance.
no code implementations • Findings (EMNLP) 2021 • Zhan Shi, Hui Liu, Martin Renqiang Min, Christopher Malon, Li Erran Li, Xiaodan Zhu
Image captioning systems are expected to have the ability to combine individual concepts when describing scenes with concept combinations that are not observed during training.
no code implementations • 12 Mar 2024 • Jiuding Yang, Hui Liu, Weidong Guo, Zhuwei Rao, Yu Xu, Di Niu
Ensuring factual consistency between the summary and the original document is paramount in summarization tasks.
no code implementations • 8 Mar 2024 • Wei Duan, Hui Liu
The development of single-cell sequencing technology had promoted the generation of a large amount of single-cell transcriptional profiles, providing valuable opportunities to explore drug-resistant cell subpopulations in a tumor.
no code implementations • 4 Mar 2024 • Jianhan Qi, Yuheng Jia, Hui Liu, Junhui Hou
The state-of-the-art (SOTA) methods usually rely on superpixels, however, they do not fully utilize the spatial and spectral information in HSI 3-D structure, and their optimization targets are not clustering-oriented.
no code implementations • 4 Mar 2024 • Yuheng Jia, Jianhong Cheng, Hui Liu, Junhui Hou
Deep clustering has exhibited remarkable performance; however, the overconfidence problem, i. e., the estimated confidence for a sample belonging to a particular cluster greatly exceeds its actual prediction accuracy, has been overlooked in prior research.
no code implementations • 26 Feb 2024 • Kefu Guo, Fengfan Zhou, Hefei Ling, Ping Li, Hui Liu
JPEG compression can significantly impair the performance of adversarial face examples, which previous adversarial attacks on face recognition (FR) have not adequately addressed.
no code implementations • 14 Feb 2024 • Hanbing Wang, Xiaorui Liu, Wenqi Fan, Xiangyu Zhao, Venkataramana Kini, Devendra Yadav, Fei Wang, Zhen Wen, Jiliang Tang, Hui Liu
This design stems from our empirical observation that beam search decoding is ultimately unnecessary for sequential recommendations.
no code implementations • 13 Feb 2024 • Li Ma, Haoyu Han, Juanhui Li, Harry Shomer, Hui Liu, Xiaofeng Gao, Jiliang Tang
Link prediction, which aims to forecast unseen connections in graphs, is a fundamental task in graph machine learning.
1 code implementation • 12 Feb 2024 • Hui Liu, Wenya Wang, Haoru Li, Haoliang Li
The proliferation of fake news has emerged as a severe societal problem, raising significant interest from industry and academia.
no code implementations • 4 Feb 2024 • Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang
We examine from two distinct viewpoints: the copyrights pertaining to the source data held by the data owners and those of the generative models maintained by the model builders.
no code implementations • 16 Jan 2024 • Linghan Zheng, Hui Liu, Xiaojun Lin, Jiayuan Dong, Yue Sheng, Gang Shi, Zhiwei Liu, Hongwei Chen
In previous studies, code-based models have consistently outperformed text-based models in reasoning-intensive scenarios.
1 code implementation • 6 Dec 2023 • Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Liang Sun, Rong Jin
Moreover, we approximate the sparse regression process using a blend of a two-layer MLP and an extensive codebook.
Ranked #5 on Traffic Prediction on BJTaxi
1 code implementation • 24 Nov 2023 • Hui Liu, Wenya Wang, Hao Sun, Anderson Rocha, Haoliang Li
We also propose a framework that simultaneously considers application scenarios of domain generalization (in which the target domain data is unavailable) and domain adaptation (in which unlabeled target domain data is available).
no code implementations • 17 Nov 2023 • Wei Huang, Aichun Zhu, Hui Liu
Phenotype-based screening has attracted much attention for identifying cell-active compounds.
no code implementations • 17 Nov 2023 • Yizhou Wang, Jen-Hao Cheng, Jui-Te Huang, Sheng-Yao Kuan, Qiqian Fu, Chiming Ni, Shengyu Hao, Gaoang Wang, Guanbin Xing, Hui Liu, Jenq-Neng Hwang
This kind of radar format can enable machine learning models to generate more reliable object perception results after interacting and fusing the information or features between the camera and radar.
no code implementations • 15 Nov 2023 • Jia Zhai, Hui Liu
This paper proposed a domain adaptation network for feature disentanglement to separate representations of cancer cells and TME of a tumor in patients.
1 code implementation • NeurIPS 2023 • Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Hui Yuan
To harness the capabilities of diffusion models, we delve into this intricate process and advocate for the regularization of its inherent ODE-trajectory.
Ranked #2 on Low-Light Image Enhancement on LOL
no code implementations • 20 Oct 2023 • Kaiqi Yang, Haoyu Han, Wei Jin, Hui Liu
Existing augmentation views with perturbed graph structures are usually based on random topology corruption in the spatial domain; however, from perspectives of the spectral domain, this approach may be ineffective as it fails to pose tailored impacts on the information of different frequencies, thus weakening the agreement between the augmentation views.
no code implementations • 15 Oct 2023 • Yuxiu Lin, Hui Liu, Ren Wang, Qiang Guo, Caiming Zhang
i) The parameter scale of the FC layer is quadratic to sample numbers, resulting in high time and memory costs that significantly degrade their feasibility in large-scale datasets.
1 code implementation • 7 Oct 2023 • Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
In light of these observations, this work introduces a label-free node classification on graphs with LLMs pipeline, LLM-GNN.
no code implementations • 3 Oct 2023 • Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang
Text-to-image generative models based on latent diffusion models (LDM) have demonstrated their outstanding ability in generating high-quality and high-resolution images according to language prompt.
1 code implementation • 2 Oct 2023 • Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, Jiliang Tang
ChatGPT is one of the most popular language models which achieve amazing performance on various natural language tasks.
1 code implementation • 19 Sep 2023 • Aiyuan Yang, Bin Xiao, Bingning Wang, Borong Zhang, Ce Bian, Chao Yin, Chenxu Lv, Da Pan, Dian Wang, Dong Yan, Fan Yang, Fei Deng, Feng Wang, Feng Liu, Guangwei Ai, Guosheng Dong, Haizhou Zhao, Hang Xu, Haoze Sun, Hongda Zhang, Hui Liu, Jiaming Ji, Jian Xie, Juntao Dai, Kun Fang, Lei Su, Liang Song, Lifeng Liu, Liyun Ru, Luyao Ma, Mang Wang, Mickel Liu, MingAn Lin, Nuolan Nie, Peidong Guo, Ruiyang Sun, Tao Zhang, Tianpeng Li, Tianyu Li, Wei Cheng, WeiPeng Chen, Xiangrong Zeng, Xiaochuan Wang, Xiaoxi Chen, Xin Men, Xin Yu, Xuehai Pan, Yanjun Shen, Yiding Wang, Yiyu Li, Youxin Jiang, Yuchen Gao, Yupeng Zhang, Zenan Zhou, Zhiying Wu
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering.
no code implementations • 22 Aug 2023 • Zengxiang Li, Zhaoxiang Hou, Hui Liu, Ying Wang, Tongzhi Li, Longfei Xie, Chao Shi, Chengyi Yang, Weishan Zhang, Zelei Liu, Liang Xu
Preliminary experiments show that enterprises can enhance and accumulate intelligent capabilities through multimodal model federated learning, thereby jointly creating an smart city model that provides high-quality intelligent services covering energy infrastructure safety, residential community security, and urban operation management.
no code implementations • 18 Jul 2023 • Jianxiang Zang, Hui Liu
Siamese networks have gained popularity as a method for modeling text semantic similarity.
no code implementations • 14 Jul 2023 • Fan Ni, Xu Zhang, Jianhui Wu, Guan-Nan Dong, Aichun Zhu, Hui Liu, Yue Zhang
To the best of our knowledge, TVPRN is the first successful attempt to use video for text-based person retrieval task and has achieved state-of-the-art performance on TVPReid dataset.
2 code implementations • 7 Jul 2023 • Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang
The most popular pipeline for learning on graphs with textual node attributes primarily relies on Graph Neural Networks (GNNs), and utilizes shallow text embedding as initial node representations, which has limitations in general knowledge and profound semantic understanding.
1 code implementation • 11 Jun 2023 • Jiatong Li, Yunqing Liu, Wenqi Fan, Xiao-Yong Wei, Hui Liu, Jiliang Tang, Qing Li
Molecule discovery plays a crucial role in various scientific fields, advancing the design of tailored materials and drugs.
Ranked #3 on Text-based de novo Molecule Generation on ChEBI-20
1 code implementation • 5 Jun 2023 • Jiabang He, Yi Hu, Lei Wang, Xing Xu, Ning Liu, Hui Liu, Heng Tao Shen
Results from the experiments demonstrate that there is a significant performance gap between the in-distribution (ID) and OOD settings for document images, and that fine-grained analysis of distribution shifts can reveal the brittle nature of existing pre-trained VDU models and OOD generalization algorithms.
no code implementations • 25 May 2023 • Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Yue Xing, Jiliang Tang
By detecting the watermark from generated images, copyright infringement can be exposed with evidence.
no code implementations • 21 May 2023 • Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang
Directly adopting existing post-hoc explainers for explaining link prediction is sub-optimal because: (i) post-hoc explainers usually adopt another strategy or model to explain a target model, which could misinterpret the target model; and (ii) GNN explainers for node classification identify crucial subgraphs around each node for the explanation; while for link prediction, one needs to explain the prediction for each pair of nodes based on graph structure and node attributes.
2 code implementations • 10 May 2023 • Hui Liu, Wenya Wang, Haoliang Li
Multimodal misinformation on online social platforms is becoming a critical concern due to increasing credibility and easier dissemination brought by multimedia content, compared to traditional text-only information.
1 code implementation • 5 May 2023 • Lei Wang, Yi Hu, Jiabang He, Xing Xu, Ning Liu, Hui Liu, Heng Tao Shen
To address these issues, we propose a novel method termed T-SciQ that aims at teaching science question answering with LLM signals.
no code implementations • 25 Apr 2023 • Yakun Yu, Jiuding Yang, Weidong Guo, Hui Liu, Yu Xu, Di Niu
In this paper, we first collect and present a real-world dataset named Short Video Title Generation (SVTG) that contains videos with appealing titles and covers.
1 code implementation • 3 Apr 2023 • Zhimeng Guo, Teng Xiao, Zongyu Wu, Charu Aggarwal, Hui Liu, Suhang Wang
To facilitate the development of this promising direction, in this survey, we categorize and comprehensively review papers on graph counterfactual learning.
1 code implementation • 26 Mar 2023 • Ji Qi, Jifan Yu, Teng Tu, Kunyu Gao, Yifan Xu, Xinyu Guan, Xiaozhi Wang, Yuxiao Dong, Bin Xu, Lei Hou, Juanzi Li, Jie Tang, Weidong Guo, Hui Liu, Yu Xu
Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i. e., long and informative commentary about the domain-specific scenes with appropriate reasoning) is still far from being solved, which however has great applications such as automatic sports narrative.
1 code implementation • ICCV 2023 • Jiabang He, Lei Wang, Yi Hu, Ning Liu, Hui Liu, Xing Xu, Heng Tao Shen
To this end, we propose a simple but effective in-context learning framework called ICL-D3IE, which enables LLMs to perform DIE with different types of demonstration examples.
no code implementations • 6 Mar 2023 • Hui Liu, Xiaojun Wan
In this work, we conduct a detailed human evaluation of the factuality in video captioning and collect two annotated factuality datasets.
1 code implementation • 1 Mar 2023 • Wenzhuo Tang, Hongzhi Wen, Renming Liu, Jiayuan Ding, Wei Jin, Yuying Xie, Hui Liu, Jiliang Tang
The recent development of multimodal single-cell technology has made the possibility of acquiring multiple omics data from individual cells, thereby enabling a deeper understanding of cellular states and dynamics.
1 code implementation • 6 Feb 2023 • Chengyi Liu, Wenqi Fan, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li
Given the great success of diffusion models in image generation, increasing efforts have been made to leverage these techniques to advance graph generation in recent years.
1 code implementation • 6 Feb 2023 • Hongzhi Wen, Wenzhuo Tang, Wei Jin, Jiayuan Ding, Renming Liu, Xinnan Dai, Feng Shi, Lulu Shang, Hui Liu, Yuying Xie
In particular, investigate the following two key questions: (1) $\textit{how to encode spatial information of cells in transformers}$, and (2) $\textit{ how to train a transformer for transcriptomic imputation}$.
1 code implementation • IEEE Transactions on Software Engineering 2023 • Leping Li, Hui Liu, Kejun Li, Yanjie Jiang, and Rui Sun
The key to such approaches is to fix a faulty program by making it equivalent to one of its correct reference programs whose overall structure is identical to that of the faulty submission.
1 code implementation • 15 Jan 2023 • Jinhui Hou, Zhiyu Zhu, Junhui Hou, Hui Liu, Huanqiang Zeng, Deyu Meng
In this paper, we study the problem of efficiently and effectively embedding the high-dimensional spatio-spectral information of hyperspectral (HS) images, guided by feature diversity.
1 code implementation • 27 Nov 2022 • Lei Wang, Jiabang He, Xing Xu, Ning Liu, Hui Liu
In this paper, we propose a new model architecture with alignment-enriched tuning (dubbed AETNet) upon pre-trained document image models, to adapt downstream tasks with the joint task-specific supervised and alignment-aware contrastive objective.
1 code implementation • 19 Nov 2022 • Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou
To begin, we leverage both semantic and topological information by employing a vanilla auto-encoder and a graph convolution network, respectively, to learn a latent feature representation.
no code implementations • 17 Nov 2022 • Sheng Guo, Zengxiang Li, Hui Liu, Shubao Zhao, Cheng Hao Jin
Intelligent fault diagnosis is essential to safe operation of machinery.
1 code implementation • 7 Nov 2022 • Hui Liu, Weidong Guo, Yige Chen, Xiangyang Li
In this paper, we propose a novel Seq2Seq model called CLH3G (Contrastive Learning enhanced Historical Headlines based Headline Generation) which can use the historical headlines of the articles that the author wrote in the past to improve the headline generation of current articles.
no code implementations • 29 Oct 2022 • Bing Mao, Xiaoqun Wu, Hui Liu, Yuhua Xu, Jinhu Lü
Adaptive fuzzy control strategies are established to achieve global prescribed performance with prescribed-time convergence for strict-feedback systems with mismatched uncertainties and unknown nonlinearities.
no code implementations • 17 Oct 2022 • Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang
To tackle this problem, we propose Probabilistic Categorical Adversarial Attack (PCAA), which transfers the discrete optimization problem to a continuous problem that can be solved efficiently by Projected Gradient Descent.
no code implementations • 16 Oct 2022 • Hui Liu, Bo Zhao, Kehuan Zhang, Peng Liu
In this paper, we propose an AutoEncoder-based Adversarial Examples (AEAE) detector, that can guard DNN models by detecting adversarial examples with low computation in an unsupervised manner.
1 code implementation • 7 Oct 2022 • Hui Liu, Wenya Wang, Haoliang Li
In this paper, we propose a novel hierarchical framework for sarcasm detection by exploring both the atomic-level congruity based on multi-head cross attention mechanism and the composition-level congruity based on graph neural networks, where a post with low congruity can be identified as sarcasm.
1 code implementation • 12 Sep 2022 • Meng You, Mantang Guo, Xianqiang Lyu, Hui Liu, Junhui Hou
To tackle this challenging problem, we propose a new deep learning-based view synthesis paradigm that learns a locally unified 3D point cloud from source views.
no code implementations • 5 Aug 2022 • Ruining Tang, Zhenyu Liu, Yangguang Li, Yiguo Song, Hui Liu, Qide Wang, Jing Shao, Guifang Duan, Jianrong Tan
To alleviate this problem, a novel Task-decoupled Feature Distillation (TFD) is proposed by flexibly balancing the contributions of classification and regression tasks.
no code implementations • 9 Jul 2022 • Jinhui Hou, Zhiyu Zhu, Hui Liu, Junhui Hou
This paper tackles the challenging problem of hyperspectral (HS) image denoising.
1 code implementation • 21 May 2022 • Yuheng Jia, Guanxing Lu, Hui Liu, Junhui Hou
In this letter, we propose a novel semi-supervised subspace clustering method, which is able to simultaneously augment the initial supervisory information and construct a discriminative affinity matrix.
no code implementations • 17 May 2022 • Yiming Fang, Xuejun Liu, Hui Liu
The limitation can be attributed to the binding specificity of T cell receptor (TCR) to peptide-MHC complex (pMHC).
no code implementations • 2 May 2022 • Hui Liu, Yibiao Huang, Xuejun Liu, Lei Deng
We developed a novel molecular graph augmentation strategy, referred to as attention-wise graph mask, to generate challenging positive sample for contrastive learning.
1 code implementation • 25 Apr 2022 • Haojie Huang, Gongming Zhou, Xuejun Liu, Lei Deng, Chen Wu, Dachuan Zhang, Hui Liu
We leveraged contrastive learning on large-scale unannotated WSIs to derive slide-level histopathological feature in latent space, and then transfer it to tumor diagnosis and prediction of differentially expressed cancer driver genes.
no code implementations • 18 Apr 2022 • Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
Despite their great potential in benefiting humans in the real world, recent study shows that GNNs can leak private information, are vulnerable to adversarial attacks, can inherit and magnify societal bias from training data and lack interpretability, which have risk of causing unintentional harm to the users and society.
2 code implementations • CVPR 2022 • Ye Yuan, Xiao Liu, Wondimu Dikubab, Hui Liu, Zhilong Ji, Zhongqin Wu, Xiang Bai
In this paper, we propose a simple and efficient method for HMER, which is the first to incorporate syntax information into an encoder-decoder network.
1 code implementation • 22 Jan 2022 • Mantang Guo, Junhui Hou, Jing Jin, Hui Liu, Huanqiang Zeng, Jiwen Lu
To this end, we propose content-aware warping, which adaptively learns the interpolation weights for pixels of a relatively large neighborhood from their contextual information via a lightweight neural network.
no code implementations • 4 Jan 2022 • Hui Liu, Bo Zhao, Yuefeng Peng, Weidong Li, Peng Liu
Experimental results show that the contribution of image transformations to adversarial detection is significantly different, the combination of them can significantly improve the generic detection ability against state-of-the-art adversarial attacks.
1 code implementation • 1 Jan 2022 • Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
To mitigate these issues, we propose a novel framework which adopts the noisy edges as supervision to learn a denoised and dense graph, which can down-weight or eliminate noisy edges and facilitate message passing of GNNs to alleviate the issue of limited labeled nodes.
no code implementations • 1 Jan 2022 • Rohan Bhambhoria, Hui Liu, Samuel Dahan, Xiaodan Zhu
In this work, we utilize deep learning models in the area of trademark law to shed light on the issue of likelihood of confusion between trademarks.
1 code implementation • 10 Nov 2021 • Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou
Existing deep embedding clustering works only consider the deepest layer to learn a feature embedding and thus fail to well utilize the available discriminative information from cluster assignments, resulting performance limitation.
no code implementations • 31 Oct 2021 • Xiangyu Gao, Hui Liu, Sumit Roy, Guanbin Xing, Ali Alansari, Youchen Luo
Detecting harmful carried objects plays a key role in intelligent surveillance systems and has widespread applications, for example, in airport security.
no code implementations • ACL 2022 • Haochen Liu, Joseph Thekinen, Sinem Mollaoglu, Da Tang, Ji Yang, Youlong Cheng, Hui Liu, Jiliang Tang
We conduct experiments on both synthetic and real-world datasets.
1 code implementation • 29 Sep 2021 • Liang Zongwei, Junan Yang, Keju Huang, Hui Liu, Lin Cui, Lingzhi Qu, Xiang Li
The interpretability of the current temporal KG forecasting models is manifested in providing the reasoning paths.
1 code implementation • 28 Sep 2021 • Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou
In this paper, we propose a novel adaptive attribute and structure subspace clustering network (AASSC-Net) to simultaneously consider the attribute and structure information in an adaptive graph fusion manner.
1 code implementation • EMNLP 2021 • Hui Liu, Zhan Shi, Xiaodan Zhu
For the message-pair classifier, we enrich its training data by retrieving message pairs with high confidence from the disentangled sessions predicted by the session classifier.
1 code implementation • ICCV 2021 • Mantang Guo, Jing Jin, Hui Liu, Junhui Hou
In this paper, we tackle the problem of dense light field (LF) reconstruction from sparsely-sampled ones with wide baselines and propose a learnable model, namely dynamic interpolation, to replace the commonly-used geometry warping operation.
1 code implementation • ICCV 2021 • Zhiyu Zhu, Hui Liu, Junhui Hou, Huanqiang Zeng, Qingfu Zhang
Specifically, on the basis of the intrinsic imaging degradation model of RGB images from HS images, we progressively spread the differences between input RGB images and re-projected RGB images from recovered HS images via effective unsupervised camera spectral response function estimation.
1 code implementation • 14 Aug 2021 • Lei Deng, Yibiao Huang, Xuejun Liu, Hui Liu
We evaluated our method on three independent datasets and the experimental results showed that our proposed method outperformed six existing state-of-the-art methods.
2 code implementations • 12 Aug 2021 • Zhihao Peng, Hui Liu, Yuheng Jia, Junhui Hou
The combination of the traditional convolutional network (i. e., an auto-encoder) and the graph convolutional network has attracted much attention in clustering, in which the auto-encoder extracts the node attribute feature and the graph convolutional network captures the topological graph feature.
1 code implementation • 12 Aug 2021 • Zhiyu Zhu, Hui Liu, Junhui Hou, Sen Jia, Qingfu Zhang
Then, we design a lightweight neural network with a multi-stage architecture to mimic the formed amended gradient descent process, in which efficient convolution and novel spectral zero-mean normalization are proposed to effectively extract spatial-spectral features for regressing an initialization, a basic gradient, and an incremental gradient.
1 code implementation • ACL 2021 • Zhan Shi, Hui Liu, Xiaodan Zhu
In this paper we propose a novel approach to encourage captioning models to produce more detailed captions using natural language inference, based on the motivation that, among different captions of an image, descriptive captions are more likely to entail less descriptive captions.
no code implementations • ACL 2021 • Hui Liu, Xiaojun Wan
Most previous methods simplify this task by using ground-truth event segments.
no code implementations • 19 Jul 2021 • Hui Liu, Bo Zhao, Minzhi Ji, Yuefeng Peng, Jiabao Guo, Peng Liu
In this paper, we reveal that imperceptible adversarial examples are the product of recessive features misleading neural networks, and an adversarial attack is essentially a kind of method to enrich these recessive features in the image.
no code implementations • 12 Jun 2021 • Xiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang
Unlike existing algorithms, the proposed controller can adaptively generate the loss probabilities for different data examples according to their varied convergence behaviors.
1 code implementation • 19 May 2021 • Jia-Chen Gu, Hui Liu, Zhen-Hua Ling, Quan Liu, Zhigang Chen, Xiaodan Zhu
Empirical studies on the Persona-Chat dataset show that the partner personas neglected in previous studies can improve the accuracy of response selection in the IMN- and BERT-based models.
no code implementations • 11 May 2021 • Yizhou Wang, Gaoang Wang, Hung-Min Hsu, Hui Liu, Jenq-Neng Hwang
Radar has long been a common sensor on autonomous vehicles for obstacle ranging and speed estimation.
1 code implementation • 1 May 2021 • Shaofeng Li, Hui Liu, Tian Dong, Benjamin Zi Hao Zhao, Minhui Xue, Haojin Zhu, Jialiang Lu
We are able to demonstrate the adversary's high success rate of attacks, while maintaining functionality for regular users, with triggers inconspicuous by the human administrators.
1 code implementation • NAACL 2021 • Hui Liu, Danqing Zhang, Bing Yin, Xiaodan Zhu
In this paper, we explore to improve pretrained models with label hierarchies on the ZS-MTC task.
1 code implementation • 2 Mar 2021 • Yuheng Jia, Hui Liu, Junhui Hou, Sam Kwong, Qingfu Zhang
Inspired by ensemble clustering that aims to seek a better clustering result from a set of clustering results, we propose self-supervised SNMF (S$^3$NMF), which is capable of boosting clustering performance progressively by taking advantage of the sensitivity to initialization characteristic of SNMF, without relying on any additional information.
no code implementations • 22 Feb 2021 • Xuanmin Cao, Songyu Qiu, Hui Liu, Danning Li
The thermal widths increase rapidly above the chiral crossover temperature $T_{cp}$, indicating the dissociations of mesons at high temperature.
High Energy Physics - Phenomenology High Energy Physics - Theory
1 code implementation • 14 Feb 2021 • Jing Jin, Mantang Guo, Junhui Hou, Hui Liu, Hongkai Xiong
Besides, to promote the effectiveness of our method trained with simulated hybrid data on real hybrid data captured by a hybrid LF imaging system, we carefully design the network architecture and the training strategy.
no code implementations • 9 Feb 2021 • Dan Cristofaro-Gardiner, Umberto Hryniewicz, Michael Hutchings, Hui Liu
It is known that every contact form on a closed three-manifold has at least two simple Reeb orbits, and a generic contact form has infinitely many.
Symplectic Geometry Dynamical Systems
1 code implementation • 9 Feb 2021 • Yizhou Wang, Zhongyu Jiang, Yudong Li, Jenq-Neng Hwang, Guanbin Xing, Hui Liu
Finally, we propose a method to evaluate the object detection performance of the RODNet.
1 code implementation • 27 Dec 2020 • Bei Li, Ziyang Wang, Hui Liu, Quan Du, Tong Xiao, Chunliang Zhang, Jingbo Zhu
We proposed a novel group-permutation based knowledge distillation approach to compressing the deep Transformer model into a shallow model.
1 code implementation • 16 Dec 2020 • Yuheng Jia, Hui Liu, Junhui Hou, Qingfu Zhang
The existing clustering ensemble methods generally construct a co-association matrix, which indicates the pairwise similarity between samples, as the weighted linear combination of the connective matrices from different base clusterings, and the resulting co-association matrix is then adopted as the input of an off-the-shelf clustering algorithm, e. g., spectral clustering.
2 code implementations • 6 Dec 2020 • Zhihao Peng, Yuheng Jia, Hui Liu, Junhui Hou, Qingfu Zhang
Furthermore, we design a novel framework to explicitly decouple the auto-encoder module and the self-expressiveness module.
3 code implementations • 13 Nov 2020 • Xiangyu Gao, Guanbin Xing, Sumit Roy, Hui Liu
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support new advanced driver-assistance systems by enabling robust and high-performance object detection, localization, as well as recognition - a key component of new environmental perception.
1 code implementation • 14 Oct 2020 • Hui Liu, Bo Zhao, Minzhi Ji, Peng Liu
Adversarial examples are well-designed input samples, in which perturbations are imperceptible to the human eyes, but easily mislead the output of deep neural networks (DNNs).
1 code implementation • EMNLP 2020 • Bei Li, Ziyang Wang, Hui Liu, Yufan Jiang, Quan Du, Tong Xiao, Huizhen Wang, Jingbo Zhu
We find that stacking layers is helpful in improving the representation ability of NMT models and adjacent layers perform similarly.
1 code implementation • EMNLP 2020 • Haochen Liu, Wentao Wang, Yiqi Wang, Hui Liu, Zitao Liu, Jiliang Tang
Extensive experiments on two real-world conversation datasets show that our framework significantly reduces gender bias in dialogue models while maintaining the response quality.
no code implementations • 2 Sep 2020 • Han Xu, Ya-Xin Li, Xiaorui Liu, Hui Liu, Jiliang Tang
Thus, in this paper, we perform the initial study about adversarial attacks on meta learning under the few-shot classification problem.
1 code implementation • 31 Aug 2020 • Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, Jiliang Tang
To address these challenges, in this paper, we propose OC4Seq, a multi-scale one-class recurrent neural network for detecting anomalies in discrete event sequences.
1 code implementation • 3 Aug 2020 • Samuel Albanie, Yang Liu, Arsha Nagrani, Antoine Miech, Ernesto Coto, Ivan Laptev, Rahul Sukthankar, Bernard Ghanem, Andrew Zisserman, Valentin Gabeur, Chen Sun, Karteek Alahari, Cordelia Schmid, Shi-Zhe Chen, Yida Zhao, Qin Jin, Kaixu Cui, Hui Liu, Chen Wang, Yudong Jiang, Xiaoshuai Hao
This report summarizes the results of the first edition of the challenge together with the findings of the participants.
no code implementations • ACL 2020 • Yue Cao, Hui Liu, Xiaojun Wan
However, it is a big challenge for the model to directly learn cross-lingual summarization as it requires learning to understand different languages and learning how to summarize at the same time.
no code implementations • 26 Jun 2020 • Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang, Weiwei Guo, Jun Shi, Sida Wang, Huiji Gao, Bo Long
Specifically, we first proposed an end-to-end differentiable framework that can calculate the weights over various dimensions for feature fields in a soft and continuous manner with an AutoML based optimization algorithm; then we derive a hard and discrete embedding component architecture according to the maximal weights and retrain the whole recommender framework.
no code implementations • 30 May 2020 • Ziyue Jia, Linfeng Yang, Zhenrong Zhang, Hui Liu, Fannie Kong
Non Intrusive Load Monitoring (NILM) or Energy Disaggregation (ED), seeks to save energy by decomposing corresponding appliances power reading from an aggregate power reading of the whole house.
no code implementations • 17 May 2020 • Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jian-Ping Wang, Jiliang Tang, Qing Li
In this work, we present our framework CopyAttack, which is a reinforcement learning based black-box attack method that harnesses real users from a source domain by copying their profiles into the target domain with the goal of promoting a subset of items.
1 code implementation • ACL 2020 • Bei Li, Hui Liu, Ziyang Wang, Yufan Jiang, Tong Xiao, Jingbo Zhu, Tongran Liu, Changliang Li
In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence.
no code implementations • 30 Apr 2020 • Yuheng Jia, Hui Liu, Junhui Hou, Sam Kwong, Qingfu Zhang
On the basis of the novel tensor low-rank norm, we formulate MVSC as a convex low-rank tensor recovery problem, which is then efficiently solved with an augmented Lagrange multiplier based method iteratively.
1 code implementation • SoftwareX 2020 • Marília Barandas, Duarte Folgado, Letícia Fernandes, Sara Santos, Mariana Abreu, Patrícia Bota, Hui Liu, Tanja Schultz, Hugo Gamboa
Time series feature extraction is one of the preliminary steps of conventional machine learning pipelines.
1 code implementation • 3 Mar 2020 • Yizhou Wang, Zhongyu Jiang, Xiangyu Gao, Jenq-Neng Hwang, Guanbin Xing, Hui Liu
Radar is usually more robust than the camera in severe driving scenarios, e. g., weak/strong lighting and bad weather.
1 code implementation • 29 Dec 2019 • Xiangyu Gao, Guanbin Xing, Sumit Roy, Hui Liu
Millimeter-wave (mmW) radars are being increasingly integrated in commercial vehicles to support new Adaptive Driver Assisted Systems (ADAS) for its ability to provide high accuracy location, velocity, and angle estimates of objects, largely independent of environmental conditions.
2 code implementations • 22 Nov 2019 • Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang, Gale Yan Huang, Zitao Liu
Robust language processing systems are becoming increasingly important given the recent awareness of dangerous situations where brittle machine learning models can be easily broken with the presence of noises.
no code implementations • 23 Oct 2019 • Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu
Specifically, we design, implement and evaluate a channel-based update algorithm for the central server in a distributed system, which selects the channels with regard to the most active features in a training loop and uploads them as learned information from local datasets.
1 code implementation • COLING 2020 • Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu, Jiliang Tang
In particular, we construct a benchmark dataset and propose quantitative measures to understand fairness in dialogue models.
no code implementations • 4 Oct 2019 • Rulin Shao, Hui Liu, Dianbo Liu
Artificial neural network has achieved unprecedented success in a wide variety of domains such as classifying, predicting and recognizing objects.
4 code implementations • 17 Sep 2019 • Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain
In this survey, we review the state of the art algorithms for generating adversarial examples and the countermeasures against adversarial examples, for the three popular data types, i. e., images, graphs and text.
no code implementations • 9 Sep 2019 • Xiangyu Zhao, Changsheng Gu, Haoshenglun Zhang, Xiwang Yang, Xiaobing Liu, Jiliang Tang, Hui Liu
However, most RL-based advertising algorithms focus on optimizing ads' revenue while ignoring the possible negative influence of ads on user experience of recommended items (products, articles and videos).
no code implementations • WS 2019 • Bei Li, Yinqiao Li, Chen Xu, Ye Lin, Jiqiang Liu, Hui Liu, Ziyang Wang, Yuhao Zhang, Nuo Xu, Zeyang Wang, Kai Feng, Hexuan Chen, Tengbo Liu, Yanyang Li, Qiang Wang, Tong Xiao, Jingbo Zhu
We participated in 13 translation directions, including 11 supervised tasks, namely EN↔{ZH, DE, RU, KK, LT}, GU→EN and the unsupervised DE↔CS sub-track.
no code implementations • NAACL 2019 • Hui Liu, Wentao Qin, Xiaojun Wan
So it is of vital importance to automatically synthesize a batch of news articles related to the event or topic into a new synthesis article (or overview article) for reader's convenience.
no code implementations • 4 May 2019 • Yuheng Jia, Hui Liu, Junhui Hou, Sam Kwong
Graph-based clustering methods have demonstrated the effectiveness in various applications.
no code implementations • 11 Feb 2019 • Xiangyu Zhao, Long Xia, Linxin Zou, Hui Liu, Dawei Yin, Jiliang Tang
With the recent prevalence of Reinforcement Learning (RL), there have been tremendous interests in developing RL-based recommender systems.
Multi-agent Reinforcement Learning Recommendation Systems +1
no code implementations • ACL 2019 • Hui Liu, Qingyu Yin, William Yang Wang
Building explainable systems is a critical problem in the field of Natural Language Processing (NLP), since most machine learning models provide no explanations for the predictions.
no code implementations • 25 May 2018 • Dan Nguyen, Xun Jia, David Sher, Mu-Han Lin, Zohaib Iqbal, Hui Liu, Steve Jiang
The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the target.