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pro vyhledávání: '"Lê Hồng Phương"'
Autor:
Bui, The Viet, Le-Hong, Phuong
The FPT.AI team participated in the SHINRA2020-ML subtask of the NTCIR-15 SHINRA task. This paper describes our method to solving the problem and discusses the official results. Our method focuses on learning cross-lingual representations, both on th
Externí odkaz:
http://arxiv.org/abs/2010.03424
This paper describes our study on using mutilingual BERT embeddings and some new neural models for improving sequence tagging tasks for the Vietnamese language. We propose new model architectures and evaluate them extensively on two named entity reco
Externí odkaz:
http://arxiv.org/abs/2006.15994
Akademický článek
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Autor:
Chi, Tho Luong, Le-Hong, Phuong
This work investigates the task-oriented dialogue problem in mixed-domain settings. We study the effect of alternating between different domains in sequences of dialogue turns using two related state-of-the-art dialogue systems. We first show that a
Externí odkaz:
http://arxiv.org/abs/1909.02265
Autor:
Le-Hong, Phuong, Le, Anh-Cuong
This paper presents an extensive comparative study of four neural network models, including feed-forward networks, convolutional networks, recurrent networks and long short-term memory networks, on two sentence classification datasets of English and
Externí odkaz:
http://arxiv.org/abs/1810.01656
Autor:
Le-Hong, Phuong, Bui, Duc-Thien
In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-qualit
Externí odkaz:
http://arxiv.org/abs/1803.00712
Autor:
Le-Hong, Phuong, Pham, Thai Hoang, Pham, Xuan Khoai, Nguyen, Thi Minh Huyen, Nguyen, Thi Luong, Nguyen, Minh Hiep
In this paper, we study semantic role labelling (SRL), a subtask of semantic parsing of natural language sentences and its application for the Vietnamese language. We present our effort in building Vietnamese PropBank, the first Vietnamese SRL corpus
Externí odkaz:
http://arxiv.org/abs/1711.10124
This paper presents an empirical study of two machine translation-based approaches for Vietnamese diacritic restoration problem, including phrase-based and neural-based machine translation models. This is the first work that applies neural-based mach
Externí odkaz:
http://arxiv.org/abs/1709.07104
This paper presents an empirical study of two widely-used sequence prediction models, Conditional Random Fields (CRFs) and Long Short-Term Memory Networks (LSTMs), on two fundamental tasks for Vietnamese text processing, including part-of-speech tagg
Externí odkaz:
http://arxiv.org/abs/1708.09163
This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity recognition (NER). Our toolkit is a combination of bidirectional Long
Externí odkaz:
http://arxiv.org/abs/1708.07241