1 code implementation • EMNLP 2021 • Xincheng Ju, Dong Zhang, Rong Xiao, Junhui Li, Shoushan Li, Min Zhang, Guodong Zhou
Therefore, in this paper, we are the first to jointly perform multi-modal ATE (MATE) and multi-modal ASC (MASC), and we propose a multi-modal joint learning approach with auxiliary cross-modal relation detection for multi-modal aspect-level sentiment analysis (MALSA).
1 code implementation • 21 Oct 2024 • Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan YAO
However, considering the essential differences between text and image modalities, the design space of language models for image generation remains underexplored.
Ranked #6 on Image Generation on ImageNet 256x256
1 code implementation • 18 Oct 2024 • Shaozhe Hao, Xuantong Liu, Xianbiao Qi, Shihao Zhao, Bojia Zi, Rong Xiao, Kai Han, Kwan-Yee K. Wong
We introduce BiGR, a novel conditional image generation model using compact binary latent codes for generative training, focusing on enhancing both generation and representation capabilities.
1 code implementation • 22 Aug 2024 • Guoting Wei, Xia Yuan, Yu Liu, Zhenhao Shang, Kelu Yao, Chao Li, Qingsen Yan, Chunxia Zhao, Haokui Zhang, Rong Xiao
Then, we propose Bidirectional Vision-Language Fusion (Bi-VLF), which includes a dual-attention fusion encoder and a multi-level text-guided Fusion Decoder.
no code implementations • 24 Apr 2024 • Yanjing Wu, Yinfu Feng, Jian Wang, WenJi Zhou, Yunan Ye, Rong Xiao, Jun Xiao
To overcome these problems, we introduce an efficient Hierarchical encoding-decoding Generative retrieval method (Hi-Gen) for large-scale personalized E-commerce search systems.
2 code implementations • 19 Feb 2024 • Hanling Yi, Feng Lin, Hongbin Li, Peiyang Ning, Xiaotian Yu, Rong Xiao
This research aims to accelerate the inference speed of large language models (LLMs) with billions of parameters.
1 code implementation • 23 Jan 2024 • Feng Lin, Hanling Yi, Hongbin Li, Yifan Yang, Xiaotian Yu, Guangming Lu, Rong Xiao
Large language models (LLMs) commonly employ autoregressive generation during inference, leading to high memory bandwidth demand and consequently extended latency.
no code implementations • 16 Oct 2023 • Chao Tao, Aoran Hu, Rong Xiao, Haifeng Li, Yuze Wang
This simplifies the domain adaption from generic to specific scenes during model reasoning processes.
1 code implementation • 14 Aug 2023 • Yu Liang, Yufeng Zhang, Shiliang Zhang, YaoWei Wang, Sheng Xiao, Rong Xiao, Xiaoyu Wang
Instance-based methods like L2 regression take into account the distribution of old features but impose strong constraints on the performance of the new model itself.
no code implementations • 1 Jul 2023 • Jiong Cai, Yong Jiang, Yue Zhang, Chengyue Jiang, Ke Yu, Jianhui Ji, Rong Xiao, Haihong Tang, Tao Wang, Zhongqiang Huang, Pengjun Xie, Fei Huang, Kewei Tu
We also show that pretraining the QE module with auto-generated QE data from user logs can further improve the overall performance.
1 code implementation • NeurIPS 2023 • Yun Yi, Haokui Zhang, Rong Xiao, Nannan Wang, Xiaoyu Wang
It can learn efficient representations from both cell-structured networks and entire networks.
no code implementations • 11 Aug 2022 • Lixin Liu, Yanling Wang, Tianming Wang, Dong Guan, Jiawei Wu, Jingxu Chen, Rong Xiao, Wenxiang Zhu, Fei Fang
Therefore, it is crucial to perform cross-domain CTR prediction to transfer knowledge from large domains to small domains to alleviate the data sparsity issue.
no code implementations • IJCAI 2022 • Xiaoyi Bao, Wang Zhongqing, Xiaotong Jiang, Rong Xiao, Shoushan Li
Furthermore, we propose a pre-trained model to integrate both syntax and semantic features for opinion tree generation.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
1 code implementation • Findings (ACL) 2022 • Yu Wan, Baosong Yang, Dayiheng Liu, Rong Xiao, Derek F. Wong, Haibo Zhang, Boxing Chen, Lidia S. Chao
Attention mechanism has become the dominant module in natural language processing models.
1 code implementation • 12 Jul 2021 • Yuxiang Zhong, Xianbiao Qi, Shanjun Li, Dengyi Gu, Yihao Chen, Peiyang Ning, Rong Xiao
In this technical report, we present our 1st place solution for the ICDAR 2021 competition on mathematical formula detection (MFD).
no code implementations • 26 May 2021 • Yong Qian, Zhongqing Wang, Rong Xiao, Chen Chen, Haihong Tang
Previous studies show effective of pre-trained language models for sentiment analysis.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • 18 May 2021 • Houyi Li, Zhihong Chen, Chenliang Li, Rong Xiao, Hongbo Deng, Peng Zhang, Yongchao Liu, Haihong Tang
PDN utilizes Trigger Net to capture the user's interest in each of his/her interacted item, and Similarity Net to evaluate the similarity between each interacted item and the target item based on these items' profile and CF information.
no code implementations • 5 May 2021 • Yelin He, Xianbiao Qi, Jiaquan Ye, Peng Gao, Yihao Chen, Bingcong Li, Xin Tang, Rong Xiao
This paper presents our solution for the ICDAR 2021 Competition on Scientific Table Image Recognition to LaTeX.
2 code implementations • 5 May 2021 • Jiaquan Ye, Xianbiao Qi, Yelin He, Yihao Chen, Dengyi Gu, Peng Gao, Rong Xiao
In our method, we divide the table content recognition task into foursub-tasks: table structure recognition, text line detection, text line recognition, and box assignment. Our table structure recognition algorithm is customized based on MASTER [1], a robust image textrecognition algorithm.
Ranked #2 on Table Recognition on PubTabNet
no code implementations • 14 Feb 2021 • Shaowei Yao, Jiwei Tan, Xi Chen, Keping Yang, Rong Xiao, Hongbo Deng, Xiaojun Wan
We propose a novel way to consider samples of different relevance confidence, and come up with a new training objective to learn a robust relevance model with desirable score distribution.
1 code implementation • 24 Sep 2020 • Yihao Chen, Xin Tang, Xianbiao Qi, Chun-Guang Li, Rong Xiao
We conduct extensive experiments on benchmark datasets for different tasks, including node classification, link prediction, graph classification and graph regression, and confirm that the learned graph normalization leads to competitive results and that the learned weights suggest the appropriate normalization techniques for the specific task.
no code implementations • 23 Sep 2020 • Bingcong Li, Xin Tang, Xianbiao Qi, Yihao Chen, Rong Xiao
Thus, we propose a lightweight scene text recognition model named Hamming OCR.
1 code implementation • 21 May 2020 • Cheng Zhao, Chenliang Li, Rong Xiao, Hongbo Deng, Aixin Sun
Given two relevant domains (e. g., Book and Movie), users may have interactions with items in one domain but not in the other domain.
1 code implementation • 21 May 2020 • Zhihong Chen, Rong Xiao, Chenliang Li, Gangfeng Ye, Haochuan Sun, Hongbo Deng
Most of ranking models are trained only with displayed items (most are hot items), but they are utilized to retrieve items in the entire space which consists of both displayed and non-displayed items (most are long-tail items).
2 code implementations • 16 Apr 2020 • Wenwen Yu, Ning Lu, Xianbiao Qi, Ping Gong, Rong Xiao
Computer vision with state-of-the-art deep learning models has achieved huge success in the field of Optical Character Recognition (OCR) including text detection and recognition tasks recently.
no code implementations • 17 Mar 2020 • Di Wu, Yihao Chen, Xianbiao Qi, Yongjian Yu, Weixuan Chen, Rong Xiao
We utilise the overlay between the accurate mask prediction and less accurate mesh prediction to iteratively optimise the direct regressed 6D pose information with a focus on translation estimation.
7 code implementations • 7 Oct 2019 • Ning Lu, Wenwen Yu, Xianbiao Qi, Yihao Chen, Ping Gong, Rong Xiao, Xiang Bai
Attention-based scene text recognizers have gained huge success, which leverages a more compact intermediate representation to learn 1d- or 2d- attention by a RNN-based encoder-decoder architecture.
no code implementations • 20 May 2019 • Jianfeng Wang, Rong Xiao, Yandong Guo, Lei Zhang
In this paper, we study the problem of object counting with incomplete annotations.
no code implementations • 7 May 2019 • Bowen Cheng, Rong Xiao, Jian-Feng Wang, Thomas Huang, Lei Zhang
We present a novel high frequency residual learning framework, which leads to a highly efficient multi-scale network (MSNet) architecture for mobile and embedded vision problems.
no code implementations • 17 Sep 2018 • Bowen Cheng, Rong Xiao, Yandong Guo, Yuxiao Hu, Jian-Feng Wang, Lei Zhang
We study in this paper how to initialize the parameters of multinomial logistic regression (a fully connected layer followed with softmax and cross entropy loss), which is widely used in deep neural network (DNN) models for classification problems.