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Found 16 papers, 2 papers with code
Multi-level Community-awareness Graph Neural Networks for Neural Machine Translation
Intuitively, the MC-GNN layer substitutes a self-attention layer at the encoder side of a transformer-based machine translation model.
Matching The Statements: A Simple and Accurate Model for Key Point Analysis
Key Point Analysis (KPA) is one of the most essential tasks in building an Opinion Summarization system, which is capable of generating key points for a collection of arguments toward a particular topic.
Advancing Vietnamese Information Retrieval with Learning Objective and Benchmark
Furthermore, we also present a new objective function based on the InfoNCE loss function, which is used to train our Vietnamese embedding model.
URAG: Implementing a Unified Hybrid RAG for Precise Answers in University Admission Chatbots -- A Case Study at HCMUT
With the rapid advancement of Artificial Intelligence, particularly in Natural Language Processing, Large Language Models (LLMs) have become pivotal in educational question-answering systems, especially university admission chatbots.
RAPID: Retrieval-Augmented Parallel Inference Drafting for Text-Based Video Event Retrieval
Retrieving events from videos using text queries has become increasingly challenging due to the rapid growth of multimedia content.
Automated Body Composition Analysis Using DAFS Express on 2D MRI Slices at L3 Vertebral Level
This study validates an automated tool for MRI-based 2D body composition analysis- (Data Analysis Facilitation Suite (DAFS) Express), comparing its automated measurements with expert manual segmentations using UK Biobank data.
Public Health in Disaster: Emotional Health and Life Incidents Extraction during Hurricane Harvey
Countless disasters have resulted from climate change, causing severe damage to infrastructure and the economy.
Cross-Data Knowledge Graph Construction for LLM-enabled Educational Question-Answering System: A Case Study at HCMUT
In today's rapidly evolving landscape of Artificial Intelligence, large language models (LLMs) have emerged as a vibrant research topic.
A Deep Learning-Based System for Automatic Case Summarization
This paper presents a deep learning-based system for efficient automatic case summarization.
Classifying Whole Slide Images: What Matters?
Recently there have been many algorithms proposed for the classification of very high resolution whole slide images (WSIs).
Semi-supervised Neural Machine Translation with Consistency Regularization for Low-Resource Languages
We also introduce a SentenceBERT-based filter to enhance the quality of augmenting data by retaining semantically similar sentence pairs.
A Multi-variable Stacked Long-Short Term Memory Network for Wind Speed Forecasting
Precisely forecasting wind speed is essential for wind power producers and grid operators.
Spatial-temporal Multi-Task Learning for Within-field Cotton Yield Prediction
Understanding and accurately predicting within-field spatial variability of crop yield play a key role in site-specific management of crop inputs such as irrigation water and fertilizer for optimized crop production.
Predicting Opioid Relapse Using Social Media Data
In this paper, we introduce a Generative Adversarial Networks (GAN) model to predict the addiction relapses based on sentiment images and social influences.
Forecasting People's Needs in Hurricane Events from Social Network
Our proposed sequence to sequence method forecast people's needs more successfully than either of the other models.
Coordinating Disaster Emergency Response with Heuristic Reinforcement Learning
To improve the efficiency of the emergency response in the immediate aftermath of a disaster, we propose a heuristic multi-agent reinforcement learning scheduling algorithm, named as ResQ, which can effectively schedule the rapid deployment of volunteers to rescue victims in dynamic settings.
Multi-agent Reinforcement Learning
reinforcement-learning
+3
