Search Results for author: Wuwei Lan

Found 7 papers, 5 papers with code

Neural semi-Markov CRF for Monolingual Word Alignment

1 code implementation ACL 2021 Wuwei Lan, Chao Jiang, Wei Xu

Monolingual word alignment is important for studying fine-grained editing operations (i. e., deletion, addition, and substitution) in text-to-text generation tasks, such as paraphrase generation, text simplification, neutralizing biased language, etc.

Paraphrase Generation Text Simplification +1

Neural CRF Model for Sentence Alignment in Text Simplification

1 code implementation ACL 2020 Chao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong, Wei Xu

The success of a text simplification system heavily depends on the quality and quantity of complex-simple sentence pairs in the training corpus, which are extracted by aligning sentences between parallel articles.

Semantic Similarity Semantic Textual Similarity +1

An Empirical Study of Pre-trained Transformers for Arabic Information Extraction

1 code implementation EMNLP 2020 Wuwei Lan, Yang Chen, Wei Xu, Alan Ritter

Multilingual pre-trained Transformers, such as mBERT (Devlin et al., 2019) and XLM-RoBERTa (Conneau et al., 2020a), have been shown to enable the effective cross-lingual zero-shot transfer.

Cross-Lingual Transfer Language Modelling +8

Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach

no code implementations8 Jul 2019 Wuwei Lan, Yanyan Xu, Bin Zhao

Travel time estimation is a crucial task for not only personal travel scheduling but also city planning.

Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering

1 code implementation COLING 2018 Wuwei Lan, Wei Xu

In this paper, we analyze several neural network designs (and their variations) for sentence pair modeling and compare their performance extensively across eight datasets, including paraphrase identification, semantic textual similarity, natural language inference, and question answering tasks.

Natural Language Inference Paraphrase Identification +2

Character-based Neural Networks for Sentence Pair Modeling

1 code implementation NAACL 2018 Wuwei Lan, Wei Xu

Sentence pair modeling is critical for many NLP tasks, such as paraphrase identification, semantic textual similarity, and natural language inference.

Natural Language Inference Paraphrase Identification +1

A Continuously Growing Dataset of Sentential Paraphrases

no code implementations EMNLP 2017 Wuwei Lan, Siyu Qiu, Hua He, Wei Xu

The main advantage of our method is its simplicity, as it gets rid of the classifier or human in the loop needed to select data before annotation and subsequent application of paraphrase identification algorithms in the previous work.

Paraphrase Identification

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