no code implementations • EMNLP 2021 • Jiawei Zhao, Wei Luo, Boxing Chen, Andrew Gilman
In this paper, we propose an alternative–a trainable mutual-learning scenario, where the MT and the ST models are collaboratively trained and are considered as peers, rather than teacher/student.
no code implementations • 24 May 2024 • Shunyu Liu, Wei Luo, Yanzhen Zhou, KaiXuan Chen, Quan Zhang, Huating Xu, Qinglai Guo, Mingli Song
Transmission interface power flow adjustment is a critical measure to ensure the security and economy operation of power systems.
1 code implementation • 16 May 2024 • Linshan Hou, Ruili Feng, Zhongyun Hua, Wei Luo, Leo Yu Zhang, Yiming Li
Deep neural networks (DNNs) are vulnerable to backdoor attacks, where adversaries can maliciously trigger model misclassifications by implanting a hidden backdoor during model training.
no code implementations • 11 Apr 2024 • Yan Pei, Wei Luo
The feature representation of an input signal is segmented into patches within the latent space, each of which is compared against the learned wave prototypes.
no code implementations • 25 Mar 2024 • Wei Luo, Bo Chen
This paper presents a novel quantization rectifier (QR) method for image compression that leverages image feature correlation to mitigate the impact of quantization.
1 code implementation • 16 Jan 2024 • Minpeng Liao, Wei Luo, Chengxi Li, Jing Wu, Kai Fan
Large language models (LLMs) have seen considerable advancements in natural language understanding tasks, yet there remains a gap to bridge before attaining true artificial general intelligence, especially concerning shortcomings in mathematical reasoning capabilities.
1 code implementation • 10 Jan 2024 • Wei Luo, Dihong Gong
Financial sentiment analysis refers to classifying financial text contents into sentiment categories (e. g. positive, negative, and neutral).
no code implementations • 5 Jan 2024 • KaiXuan Chen, Wei Luo, Shunyu Liu, Yaoquan Wei, Yihe Zhou, Yunpeng Qing, Quan Zhang, Jie Song, Mingli Song
In this paper, we present a novel transformer architecture tailored for learning robust power system state representations, which strives to optimize power dispatch for the power flow adjustment across different transmission sections.
1 code implementation • 27 Nov 2023 • Yan Pei, Jiahui Xu, Qianhao Chen, Chenhao Wang, Feng Yu, Lisan Zhang, Wei Luo
Finally, a Decoder layer is employed to reconstruct the artifact-reduced EEG signal.
no code implementations • 23 Oct 2023 • Libo Zhao, Kai Fan, Wei Luo, Jing Wu, Shushu Wang, Ziqian Zeng, Zhongqiang Huang
Simultaneous machine translation (SiMT) requires a robust read/write policy in conjunction with a high-quality translation model.
no code implementations • 5 Sep 2023 • Wei Luo, Siyuan Kang, Sheng Hu, Lixian Su, Rui Dai
However, the worldwide lockdowns over pandemic have reversed this trend as, over this period, the U. S. effectively imported more goods directly from China and indirectly through Southeast Asian exporters that imported from China.
no code implementations • 20 May 2023 • Bing Liu, Wei Luo, Gang Li, Jing Huang, Bo Yang
As deep learning gains popularity in modelling dynamical systems, we expose an underappreciated misunderstanding relevant to modelling dynamics on networks.
no code implementations • 31 Mar 2023 • Haiming Yao, Wei Luo, Wenyong Yu
In this paper, we introduce the novel state-of-the-art Dual-attention Transformer and Discriminative Flow (DADF) framework for visual anomaly detection.
Ranked #15 on Anomaly Detection on MVTec LOCO AD
1 code implementation • 28 Mar 2023 • Deze Wang, Boxing Chen, Shanshan Li, Wei Luo, Shaoliang Peng, Wei Dong, Xiangke Liao
To alleviate the potentially catastrophic forgetting issue in multilingual models, we fix all pre-trained model parameters, insert the parameter-efficient structure adapter, and fine-tune it.
no code implementations • 10 Mar 2023 • Haiming Yao, Wenyong Yu, Wei Luo, Zhenfeng Qiang, Donghao Luo, Xiaotian Zhang
To address this issue, we propose a two-branch approach that consists of a local branch for detecting structural anomalies and a global branch for detecting logical anomalies.
Ranked #17 on Anomaly Detection on MVTec LOCO AD
no code implementations • 6 Jan 2023 • Liu Liu, Yukai Lin, Xiao Liang, Qichao Xu, Miao Jia, Yangdong Liu, Yuxiang Wen, Wei Luo, Jiangwei Li
Second, a single-image-based localization pipeline (retrieval--matching--PnP) is performed to estimate 6-DoF camera poses for each query image, one for each 3D map.
no code implementations • 18 Nov 2022 • Wei Luo, Haiming Yao, Wenyong Yu
Unlike most reconstruction-based methods, our NDP-Net first employs an encoding module that extracts multi scale discriminative features of the surface textures, which is augmented with the defect discriminative ability by the proposed artificial defects and the novel pixel-level defect perception loss.
1 code implementation • 18 Oct 2022 • Chen Wang, Yuchen Liu, Boxing Chen, Jiajun Zhang, Wei Luo, Zhongqiang Huang, Chengqing Zong
Existing zero-shot methods fail to align the two modalities of speech and text into a shared semantic space, resulting in much worse performance compared to the supervised ST methods.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • 8 Aug 2022 • Wei Luo, Tongzhi Niu, Lixin Tang, Wenyong Yu, Bin Li
At first, we propose a novel clear memory-augmented module (CMAM), which combines the encoding and memoryencoding in a way of forgetting and inputting, thereby repairing abnormal foregrounds and preserving clear backgrounds.
no code implementations • 4 Mar 2022 • Qiaoling Chen, Zhihao Chen, Wei Luo
Moreover, FTM can be effectively learned on target domain in the case of few training data available and is agnostic to specific network structures.
no code implementations • 12 Oct 2021 • Akib Mashrur, Wei Luo, Nayyar A. Zaidi, Antonio Robles-Kelly
Deep neural networks tend to underestimate uncertainty and produce overly confident predictions.
no code implementations • 6 Oct 2021 • Taige Zhao, XiangYu Song, JianXin Li, Wei Luo, Imran Razzak
We first propose a graph augmentation-based partition (GAD-Partition) that can divide original graph into augmented subgraphs to reduce communication by selecting and storing as few significant nodes of other processors as possible while guaranteeing the accuracy of the training.
1 code implementation • 25 Aug 2021 • Yuqing Song, ShiZhe Chen, Qin Jin, Wei Luo, Jun Xie, Fei Huang
Firstly, there are many specialized jargons in the product description, which are ambiguous to translate without the product image.
no code implementations • 24 Dec 2020 • Weikui Ye, Zhaoyang Yin, Wei Luo
Combining \cite{wbx, ns7, ns2}, we deduce that $\dot{B}^{\frac{d}{p}-1}_{p,\infty}$ with $1\leq p<\infty$ is the critical space which solutions are ill-posedness, while $u\in\dot{B}^{\frac{d}{p}-1}_{p, r}$ with $1\leq r, p<\infty$ are well-poseness.
Analysis of PDEs
no code implementations • 9 Aug 2020 • Lei Wang, Jing Ren, Bo Xu, Jian-Xin Li, Wei Luo, Feng Xia
Link prediction plays an important role in network analysis and applications.
2 code implementations • 24 Jun 2020 • Wei Luo, Hengmin Zhang, Jun Li, Xiu-Shen Wei
We aim to provide a computationally cheap yet effective approach for fine-grained image classification (FGIC) in this letter.
Ranked #15 on Fine-Grained Image Classification on Stanford Dogs
no code implementations • ICCV 2019 • Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry S. Davis, Jun Li, Jian Yang, Ser-Nam Lim
Recognizing objects from subcategories with very subtle differences remains a challenging task due to the large intra-class and small inter-class variation.
Ranked #19 on Fine-Grained Image Classification on NABirds (using extra training data)
Fine-Grained Image Classification Fine-Grained Visual Categorization
1 code implementation • 6 Aug 2019 • Longteng Guo, Jing Liu, Jinhui Tang, Jiangwei Li, Wei Luo, Hanqing Lu
Image captioning attempts to generate a sentence composed of several linguistic words, which are used to describe objects, attributes, and interactions in an image, denoted as visual semantic units in this paper.
no code implementations • 29 Apr 2019 • Wei Luo, Feng Yu
Learning long-term dependencies still remains difficult for recurrent neural networks (RNNs) despite their success in sequence modeling recently.
no code implementations • SEMEVAL 2018 • Zhongbo Yin, Zhunchen Luo, Wei Luo, Mao Bin, Changhai Tian, Yuming Ye, Shuai Wu
We experimented on this task with two methods: CNN method and traditional pipeline method.
no code implementations • 1 May 2017 • Wei Luo, Lingzhou Xue, Jiawei Yao, Xiufan Yu
Assuming that the predictors affect the response through the latent factors, we propose to first conduct factor analysis and then apply sufficient dimension reduction on the estimated factors, to derive the reduced data for subsequent forecasting.
no code implementations • 2 Dec 2016 • Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh
In this paper, we consider the patient similarity matching problem over a cancer cohort of more than 220, 000 patients.
no code implementations • 28 Jul 2016 • Truyen Tran, Wei Luo, Dinh Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh
Preterm births occur at an alarming rate of 10-15%.
no code implementations • 2 Feb 2016 • Yiqiao Cai, Jiahai Wang, Yonghong Chen, Tian Wang, Hui Tian, Wei Luo
In most of the DE algorithms, the neighborhood and direction information are not fully and simultaneously exploited to guide the search.
no code implementations • 20 Dec 2013 • Jun Li, Wei Luo, Jian Yang, Xiao-Tong Yuan
It is well known that direct training of deep neural networks will generally lead to poor results.