no code implementations • EMNLP 2020 • Dhanasekar Sundararaman, Shijing Si, Vivek Subramanian, Guoyin Wang, Devamanyu Hazarika, Lawrence Carin
We propose a new methodology to assign and learn embeddings for numbers.
no code implementations • 23 Feb 2024 • Yuwei Wu, Shijing Si, Yugui Zhang, Jiawen Gu, Jedrek Wosik
To fill in the gap, this study attempts to evaluate ChatGPT's capabilities for spam identification in both English and Chinese email datasets.
no code implementations • 23 Dec 2023 • Shijing Si, Siqing Zhou, Le Tang, Xiaoqing Cheng, Yugui Zhang
ChatGPT's proficiency in handling modern standard languages suggests potential for its use in understanding ancient Chinese.
no code implementations • 11 Dec 2023 • Yijie Gao, Shijing Si, Hua Luo, Haixia Sun, Yugui Zhang
Label smoothing is a widely used technique in various domains, such as text classification, image classification and speech recognition, known for effectively combating model overfitting.
no code implementations • 15 Mar 2023 • Tong Ye, Shijing Si, Jianzong Wang, Ning Cheng, Zhitao Li, Jing Xiao
Deep neural retrieval models have amply demonstrated their power but estimating the reliability of their predictions remains challenging.
1 code implementation • 31 Oct 2022 • Zexuan Qiu, Qinliang Su, Jianxing Yu, Shijing Si
Efficient document retrieval heavily relies on the technique of semantic hashing, which learns a binary code for every document and employs Hamming distance to evaluate document distances.
no code implementations • 23 Oct 2022 • Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin
Weight pruning is among the most popular approaches for compressing deep convolutional neural networks.
no code implementations • 7 Oct 2022 • Jianhan Wu, Jianzong Wang, Shijing Si, Xiaoyang Qu, Jing Xiao
Most existing methods encode the texture of the whole reference human image into a latent space, and then utilize a decoder to synthesize the image texture of the target pose.
no code implementations • 30 Sep 2022 • Zihao Cao, Jianzong Wang, Shijing Si, Zhangcheng Huang, Jing Xiao
Even when data is removed from the dataset, the effects of these data persist in the model.
no code implementations • 30 Sep 2022 • Wen Wang, Jianzong Wang, Shijing Si, Zhangcheng Huang, Jing Xiao
The extraction of sequence patterns from a collection of functionally linked unlabeled DNA sequences is known as DNA motif discovery, and it is a key task in computational biology.
no code implementations • 21 Sep 2022 • Shijing Si, Jianzong Wang, xulong Zhang, Xiaoyang Qu, Ning Cheng, Jing Xiao
Nonparallel multi-domain voice conversion methods such as the StarGAN-VCs have been widely applied in many scenarios.
no code implementations • 24 Aug 2022 • Zhitao Zhu, Shijing Si, Jianzong Wang, Yaodong Yang, Jing Xiao
Deep neural networks can capture the intricate interaction history information between queries and documents, because of their many complicated nonlinear units, allowing them to provide correct search recommendations.
1 code implementation • 27 Jun 2022 • Tong Ye, Shijing Si, Jianzong Wang, Ning Cheng, Jing Xiao
In this work, we investigate the uncertainty calibration for deep audio classifiers.
no code implementations • 26 May 2022 • Shijing Si, Jianzong Wang, Ruiyi Zhang, Qinliang Su, Jing Xiao
Non-negative matrix factorization (NMF) based topic modeling is widely used in natural language processing (NLP) to uncover hidden topics of short text documents.
no code implementations • 26 May 2022 • Jianzong Wang, Shijing Si, Zhitao Zhu, Xiaoyang Qu, Zhenhou Hong, Jing Xiao
The experiments on four programming languages (Java, C, Python, and JavaScript) show that CPR can generate causal graphs for reasonable interpretations and boost the performance of bug fixing in automatic program repair.
no code implementations • 26 May 2022 • Zhengyang Li, Shijing Si, Jianzong Wang, Jing Xiao
To address this issue, we propose a framework, FedSplitBERT, which handles heterogeneous data and decreases the communication cost by splitting the BERT encoder layers into local part and global part.
no code implementations • 26 May 2022 • Yaqi Sun, Shijing Si, Jianzong Wang, Yuhan Dong, Zhitao Zhu, Jing Xiao
More importantly, we apply the Gini coefficient and validation accuracy of clients in each communication round to construct a reward function for the reinforcement learning.
no code implementations • 26 May 2022 • Zhitao Zhu, Shijing Si, Jianzong Wang, Jing Xiao
Specific to recommendation systems, many federated recommendation algorithms have been proposed to realize the privacy-preserving collaborative recommendation.
no code implementations • 25 May 2022 • Jianhan Wu, Shijing Si, Jianzong Wang, Jing Xiao
In this paper, we propose a consistency regularization framework based on data augmentation, called CR-Aug, which forces the output distributions of different sub models generated by data augmentation to be consistent with each other.
no code implementations • 24 May 2022 • Jianhan Wu, Shijing Si, Jianzong Wang, Jing Xiao
And the second is that the training of GAN is unstable and slow to converge, such as model collapse.
no code implementations • 23 Feb 2022 • Shijing Si, Jianzong Wang, Junqing Peng, Jing Xiao
To address this, we utilize the ambiguous information among the age labels, convert each age label into a discrete label distribution and leverage the label distribution learning (LDL) method to fit the data.
no code implementations • 22 Feb 2022 • Tong Ye, Shijing Si, Jianzong Wang, Rui Wang, Ning Cheng, Jing Xiao
The visual dialog task attempts to train an agent to answer multi-turn questions given an image, which requires the deep understanding of interactions between the image and dialog history.
no code implementations • 10 Jul 2021 • Shijing Si, Jianzong Wang, Xiaoyang Qu, Ning Cheng, Wenqi Wei, Xinghua Zhu, Jing Xiao
This paper investigates a novel task of talking face video generation solely from speeches.
no code implementations • ICLR 2021 • Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin
Pretrained text encoders, such as BERT, have been applied increasingly in various natural language processing (NLP) tasks, and have recently demonstrated significant performance gains.
no code implementations • 2 Jan 2021 • Yehua Wei, Lei Zhang, Ruiyi Zhang, Shijing Si, Hao Zhang, Lawrence Carin
Flexibility design problems are a class of problems that appear in strategic decision-making across industries, where the objective is to design a ($e. g.$, manufacturing) network that affords flexibility and adaptivity.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Rui Wang, Shijing Si, Guoyin Wang, Lei Zhang, Lawrence Carin, Ricardo Henao
Pretrained Language Models (PLMs) have improved the performance of natural language understanding in recent years.
1 code implementation • 22 Jun 2020 • Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Ricardo Henao, Lawrence Carin
Small and imbalanced datasets commonly seen in healthcare represent a challenge when training classifiers based on deep learning models.
no code implementations • 12 Jun 2020 • Shijing Si, Chris. J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol
Control variates are a well-established tool to reduce the variance of Monte Carlo estimators.
no code implementations • 10 Nov 2019 • Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang, Shijing Si, Dinghan Shen, Dong Wang, Lawrence Carin
Attention-based models have shown significant improvement over traditional algorithms in several NLP tasks.