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Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models
Large language models with billions of parameters, such as GPT-3. 5, GPT-4, and LLaMA, are increasingly prevalent.
NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models
This paper describes the NOWJ1 Team's approach for the Automated Legal Question Answering Competition (ALQAC) 2023, which focuses on enhancing legal task performance by integrating classical statistical models and Pre-trained Language Models (PLMs).
Constructing a Knowledge Graph for Vietnamese Legal Cases with Heterogeneous Graphs
This paper presents a knowledge graph construction method for legal case documents and related laws, aiming to organize legal information efficiently and enhance various downstream tasks.
RMDM: A Multilabel Fakenews Dataset for Vietnamese Evidence Verification
In this study, we present a novel and challenging multilabel Vietnamese dataset (RMDM) designed to assess the performance of large language models (LLMs), in verifying electronic information related to legal contexts, focusing on fake news as potential input for electronic evidence.
NeCo@ALQAC 2023: Legal Domain Knowledge Acquisition for Low-Resource Languages through Data Enrichment
In recent years, natural language processing has gained significant popularity in various sectors, including the legal domain.
Improving Vietnamese Legal Question--Answering System based on Automatic Data Enrichment
Question answering (QA) in law is a challenging problem because legal documents are much more complicated than normal texts in terms of terminology, structure, and temporal and logical relationships.
NOWJ at COLIEE 2023 -- Multi-Task and Ensemble Approaches in Legal Information Processing
This paper presents the NOWJ team's approach to the COLIEE 2023 Competition, which focuses on advancing legal information processing techniques and applying them to real-world legal scenarios.
LBMT team at VLSP2022-Abmusu: Hybrid method with text correlation and generative models for Vietnamese multi-document summarization
Multi-document summarization is challenging because the summaries should not only describe the most important information from all documents but also provide a coherent interpretation of the documents.
Non-Standard Vietnamese Word Detection and Normalization for Text-to-Speech
In the second phase, we propose a forward lexicon-based maximum matching algorithm to split down the hashtag, email, URL, and contact name.
Transformer-based Approaches for Legal Text Processing
In this paper, we introduce our approaches using Transformer-based models for different problems of the COLIEE 2021 automatic legal text processing competition.
ParaLaw Nets -- Cross-lingual Sentence-level Pretraining for Legal Text Processing
Ambiguity is a characteristic of natural language, which makes expression ideas flexible.
JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021
COLIEE is an annual competition in automatic computerized legal text processing.
