Search Results for author: Haitao Mi

Found 16 papers, 3 papers with code

A Dialogue-based Information Extraction System for Medical Insurance Assessment

no code implementations13 Jul 2021 Shuang Peng, Mengdi Zhou, Minghui Yang, Haitao Mi, Shaosheng Cao, Zujie Wen, Teng Xu, Hongbin Wang, Lei Liu

In the Chinese medical insurance industry, the assessor's role is essential and requires significant efforts to converse with the claimant.

R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling

1 code implementation ACL 2021 Xiang Hu, Haitao Mi, Zujie Wen, Yafang Wang, Yi Su, Jing Zheng, Gerard de Melo

Human language understanding operates at multiple levels of granularity (e. g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combined.

Language Modelling

Multi-Perspective Context Matching for Machine Comprehension

1 code implementation13 Dec 2016 Zhiguo Wang, Haitao Mi, Wael Hamza, Radu Florian

Based on this dataset, we propose a Multi-Perspective Context Matching (MPCM) model, which is an end-to-end system that directly predicts the answer beginning and ending points in a passage.

Question Answering Reading Comprehension

Temporal Attention Model for Neural Machine Translation

no code implementations9 Aug 2016 Baskaran Sankaran, Haitao Mi, Yaser Al-Onaizan, Abe Ittycheriah

Attention-based Neural Machine Translation (NMT) models suffer from attention deficiency issues as has been observed in recent research.

Machine Translation

Supervised Attentions for Neural Machine Translation

no code implementations EMNLP 2016 Haitao Mi, Zhiguo Wang, Abe Ittycheriah

We simply compute the distance between the machine attentions and the "true" alignments, and minimize this cost in the training procedure.

Machine Translation

Vocabulary Manipulation for Neural Machine Translation

no code implementations ACL 2016 Haitao Mi, Zhiguo Wang, Abe Ittycheriah

Our method simply takes into account the translation options of each word or phrase in the source sentence, and picks a very small target vocabulary for each sentence based on a word-to-word translation model or a bilingual phrase library learned from a traditional machine translation model.

Machine Translation

Coverage Embedding Models for Neural Machine Translation

no code implementations EMNLP 2016 Haitao Mi, Baskaran Sankaran, Zhiguo Wang, Abe Ittycheriah

In this paper, we enhance the attention-based neural machine translation (NMT) by adding explicit coverage embedding models to alleviate issues of repeating and dropping translations in NMT.

Machine Translation

Sentence Similarity Learning by Lexical Decomposition and Composition

1 code implementation COLING 2016 Zhiguo Wang, Haitao Mi, Abraham Ittycheriah

Most conventional sentence similarity methods only focus on similar parts of two input sentences, and simply ignore the dissimilar parts, which usually give us some clues and semantic meanings about the sentences.

Paraphrase Identification Question Answering +1

Semi-supervised Clustering for Short Text via Deep Representation Learning

no code implementations CONLL 2016 Zhiguo Wang, Haitao Mi, Abraham Ittycheriah

In this work, we propose a semi-supervised method for short text clustering, where we represent texts as distributed vectors with neural networks, and use a small amount of labeled data to specify our intention for clustering.

Representation Learning Short Text Clustering

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