Search Results for author: Tho Quan

Found 7 papers, 2 papers with code

Grounding Language Representation with Visual Object Information via Cross Modal Pretraining

no code implementations29 Sep 2021 Cong-Duy T Nguyen, Anh Tuan Luu, Tho Quan

However, this approach has two main drawbacks: (i) the whole image usually contains more objects and backgrounds than the sentence itself; thus, matching them together will confuse the grounded model; (ii) CNN only extracts the features of the image but not the relationship between objects inside that, limiting the grounded model to learn complicated contexts.

Grounded language learning

Enriching and Controlling Global Semantics for Text Summarization

no code implementations EMNLP 2021 Thong Nguyen, Anh Tuan Luu, Truc Lu, Tho Quan

Recently, Transformer-based models have been proven effective in the abstractive summarization task by creating fluent and informative summaries.

Abstractive Text Summarization Text Generation

PageRank algorithm for Directed Hypergraph

no code implementations29 Aug 2019 Loc Tran, Tho Quan, An Mai

In this paper, we will model the World Wide Web's link structure as the directed hypergraph.

Nested Variational Autoencoder for Topic Modeling on Microtexts with Word Vectors

1 code implementation1 May 2019 Trung Trinh, Tho Quan, Trung Mai

The objective of our research is to create a topic model that can achieve great performances on microtexts while requiring a small runtime for scalability to large datasets.

Topic Models Word Embeddings

Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media

no code implementations16 Feb 2019 Khuong Vo, Tri Nguyen, Dang Pham, Mao Nguyen, Minh Truong, Trung Mai, Tho Quan

However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels.

Data Augmentation Natural Language Processing +3

Towards Autoencoding Variational Inference for Aspect-based Opinion Summary

1 code implementation7 Feb 2019 Tai Hoang, Huy Le, Tho Quan

Firstly, we introduce the Autoencoding Variational Inference for Aspect Discovery (AVIAD) model, which extends the previous work of Autoencoding Variational Inference for Topic Models (AVITM) to embed prior knowledge of seed words.

General Classification Sentiment Analysis +2

Combination of Domain Knowledge and Deep Learning for Sentiment Analysis

no code implementations22 Jun 2018 Khuong Vo, Dang Pham, Mao Nguyen, Trung Mai, Tho Quan

In particular, when analyzing the applications of deep learning in sentiment analysis, we found that the current approaches are suffering from the following drawbacks: (i) the existing works have not paid much attention to the importance of different types of sentiment terms, which is an important concept in this area; and (ii) the loss function currently employed does not well reflect the degree of error of sentiment misclassification.

Sentiment Analysis

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