Search Results for author: Weidi Xu

Found 6 papers, 2 papers with code

LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints

no code implementations27 Sep 2023 Weidi Xu, Jingwei Wang, Lele Xie, Jianshan He, Hongting Zhou, Taifeng Wang, Xiaopei Wan, Jingdong Chen, Chao Qu, Wei Chu

Integrating first-order logic constraints (FOLCs) with neural networks is a crucial but challenging problem since it involves modeling intricate correlations to satisfy the constraints.

Variational Inference

Question Directed Graph Attention Network for Numerical Reasoning over Text

no code implementations EMNLP 2020 Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi, Wei Chu

Numerical reasoning over texts, such as addition, subtraction, sorting and counting, is a challenging machine reading comprehension task, since it requires both natural language understanding and arithmetic computation.

Graph Attention Machine Reading Comprehension +2

SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Check

1 code implementation ACL 2020 Xingyi Cheng, Weidi Xu, Kunlong Chen, Shaohua Jiang, Feng Wang, Taifeng Wang, Wei Chu, Yuan Qi

This paper proposes to incorporate phonological and visual similarity knowledge into language models for CSC via a specialized graph convolutional network (SpellGCN).

Symmetric Regularization based BERT for Pair-wise Semantic Reasoning

1 code implementation8 Sep 2019 Weidi Xu, Xingyi Cheng, Kunlong Chen, Wei Wang, Bin Bi, Ming Yan, Chen Wu, Luo Si, Wei Chu, Taifeng Wang

To remedy this, we propose to augment the NSP task to a 3-class categorization task, which includes a category for previous sentence prediction (PSP).

Machine Reading Comprehension Natural Language Inference +1

Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer

no code implementations CONLL 2019 Xingyi Cheng, Weidi Xu, Taifeng Wang, Wei Chu

By disentangling the latent representation into the aspect-specific sentiment and the lexical context, our method induces the underlying sentiment prediction for the unlabeled data, which then benefits the ATSA classifier.

Aspect-Based Sentiment Analysis (ABSA) Natural Language Understanding +1

Variational Autoencoders for Semi-supervised Text Classification

no code implementations8 Mar 2016 Weidi Xu, Haoze Sun, Chao Deng, Ying Tan

Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classification task if using vanilla LSTM as its decoder.

General Classification Image Classification +2

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