Search Results for author: Minh Le Nguyen

Found 20 papers, 4 papers with code

Encoded Summarization: Summarizing Documents into Continuous Vector Space for Legal Case Retrieval

no code implementations15 Sep 2023 Vu Tran, Minh Le Nguyen, Satoshi Tojo, Ken Satoh

We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep neural networks.

Retrieval

Causal Intersectionality and Dual Form of Gradient Descent for Multimodal Analysis: a Case Study on Hateful Memes

no code implementations19 Aug 2023 Yosuke Miyanishi, Minh Le Nguyen

In the wake of the explosive growth of machine learning (ML) usage, particularly within the context of emerging Large Language Models (LLMs), comprehending the semantic significance rooted in their internal workings is crucial.

Decision Making In-Context Learning

PhraseTransformer: An Incorporation of Local Context Information into Sequence-to-sequence Semantic Parsing

1 code implementation Applied Intelligence 2022 Phuong Minh Nguyen, Tung Le, Huy Tien Nguyen, Vu Tran, Minh Le Nguyen

In addition, to prove the generalization of our proposed model, we also conduct extensive experiments on three translation datasets IWLST14 German-English, IWSLT15 Vietnamese-English, WMT14 English-German, and show significant improvement.

Machine Translation NMT +3

Miko Team: Deep Learning Approach for Legal Question Answering in ALQAC 2022

no code implementations4 Nov 2022 Hieu Nguyen Van, Dat Nguyen, Phuong Minh Nguyen, Minh Le Nguyen

We introduce efficient deep learning-based methods for legal document processing including Legal Document Retrieval and Legal Question Answering tasks in the Automated Legal Question Answering Competition (ALQAC 2022).

Information Retrieval Question Answering +1

PhraseTransformer: Self-Attention using Local Context for Semantic Parsing

1 code implementation1 Jan 2021 Phuong Minh Nguyen, Vu Tran, Minh Le Nguyen

Semantic parsing is a challenging task whose purpose is to convert a natural language utterance to machine-understandable information representation.

Machine Translation Semantic Parsing +2

Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model

no code implementations29 Sep 2020 Vu Tran, Minh Le Nguyen, Ken Satoh

On one hand, we adopt a summarization based model called encoded summarization which encodes a given document into continuous vector space which embeds the summary properties of the document.

Retrieval

Automatic Catchphrase Extraction from Legal Case Documents via Scoring using Deep Neural Networks

no code implementations14 Sep 2018 Vu Tran, Minh Le Nguyen, Ken Satoh

In this paper, we present a method of automatic catchphrase extracting from legal case documents.

Convolutional Neural Networks over Control Flow Graphs for Software Defect Prediction

1 code implementation14 Feb 2018 Anh Viet Phan, Minh Le Nguyen, Lam Thu Bui

Existing defects in software components is unavoidable and leads to not only a waste of time and money but also many serious consequences.

An Ensemble Method with Sentiment Features and Clustering Support

no code implementations IJCNLP 2017 Huy Tien Nguyen, Minh Le Nguyen

Deep learning models have recently been applied successfully in natural language processing, especially sentiment analysis.

Clustering General Classification +3

Building Lexical Vector Representations from Concept Definitions

no code implementations EACL 2017 Danilo Silva de Carvalho, Minh Le Nguyen

The results also indicate noticeable performance gains when combining distributional similarity scores with the ones obtained using this approach.

Dependency Parsing Machine Translation +4

Lexical-Morphological Modeling for Legal Text Analysis

no code implementations3 Sep 2016 Danilo S. Carvalho, Minh-Tien Nguyen, Tran Xuan Chien, Minh Le Nguyen

In the context of the Competition on Legal Information Extraction/Entailment (COLIEE), we propose a method comprising the necessary steps for finding relevant documents to a legal question and deciding on textual entailment evidence to provide a correct answer.

Information Retrieval Language Modelling +3

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