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Found 19 papers, 2 papers with code
GPTs and Language Barrier: A Cross-Lingual Legal QA Examination
In this paper, we explore the application of Generative Pre-trained Transformers (GPTs) in cross-lingual legal Question-Answering (QA) systems using the COLIEE Task 4 dataset.
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.
Balancing Exploration and Exploitation in LLM using Soft RLLF for Enhanced Negation Understanding
Finetuning approaches in NLP often focus on exploitation rather than exploration, which may lead to suboptimal models.
Enhancing Logical Reasoning in Large Language Models to Facilitate Legal Applications
Language serves as a vehicle for conveying thought, enabling communication among individuals.
Encoded Summarization: Summarizing Documents into Continuous Vector Space for Legal Case Retrieval
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.
Black-Box Analysis: GPTs Across Time in Legal Textual Entailment Task
The evolution of Generative Pre-trained Transformer (GPT) models has led to significant advancements in various natural language processing applications, particularly in legal textual entailment.
A negation detection assessment of GPTs: analysis with the xNot360 dataset
Negation is a fundamental aspect of natural language, playing a critical role in communication and comprehension.
Law to Binary Tree -- An Formal Interpretation of Legal Natural Language
First, legal reasoning can be performed on the basis of the binary tree representation of the regulations.
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.
JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021
COLIEE is an annual competition in automatic computerized legal text processing.
ParaLaw Nets -- Cross-lingual Sentence-level Pretraining for Legal Text Processing
Ambiguity is a characteristic of natural language, which makes expression ideas flexible.
CovRelex: A COVID-19 Retrieval System with Relation Extraction
This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers.
JNLP Team: Deep Learning for Legal Processing in COLIEE 2020
We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020.
Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model
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.
Automatic Catchphrase Extraction from Legal Case Documents via Scoring using Deep Neural Networks
In this paper, we present a method of automatic catchphrase extracting from legal case documents.
ConvAMR: Abstract meaning representation parsing for legal document
Convolutional neural networks (CNN) have recently achieved remarkable performance in a wide range of applications.
Abstract Argumentation / Persuasion / Dynamics
The act of persuasion, a key component in rhetoric argumentation, may be viewed as a dynamics modifier.
Coalition Formability Semantics with Conflict-Eliminable Sets of Arguments
As is also commonly understood, however, a coalition may deliver benefits to a group X at the sacrifice of something that X was able to do before coalition formation, which X may be no longer able to do under the coalition.
An Architecture for Autonomously Controlling Robot with Embodiment in Real World
In the real world, robots with embodiment face various issues such as dynamic continuous changes of the environment and input/output disturbances.
