18 citations · 28 across the 44 of their papers we have counts for
7 papers · 1 filter
DREAM: Dynamic Resolution Assignment For Multimodal Multi-agent Debate
Khanh-Binh Nguyen, Van Dai Do, Tien Anh Nguyen +2
Multi-agent debate (MAD) has emerged as an effective paradigm to improve the reasoning capabilities of large language models (LLMs) and is increasingly being extended to multimodal…
A Statistical Approach to Estimating Sample Size of Machine Learning Models
Dat Phan-Trong, Sunil Gupta, Svetha Venkatesh
Sample size determination for machine learning (ML) prediction models is challenging because conventional power analysis typically requires the predictor-outcome relationship and e…
Creative Generation via Multi-Agent Debate: Does Debate Suppress Diversity?
Tien Anh Nguyen, Khanh-Binh Nguyen, Van Dai Do +2
Creative generation tasks, such as narrative writing and scientific ideation, demand both high-quality outputs and distinct responses across independent runs to maximize exploratio…
Predicting Symptoms of Amotivation and Anhedonia among University Students with a Novel Oversampling Method
Dang Nguyen, Bao Duong, Arun Kumar +12
University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social functioning, and overall well…
SMOTE-VAR: An Uncertainty-Aware Oversampling Method for Predicting Depression Remission in University Students
Dang Nguyen, Arun Kumar A, Taylor A. Braund +8
University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social functioning, and overall well…
Continual Fine-Tuning of Large Language Models via Program Memory
Hung Le, Svetha Venkatesh
Parameter-Efficient Fine-Tuning (PEFT), particularly Low-Rank Adaptation (LoRA), has become a standard approach for adapting Large Language Models (LLMs) under limited compute. How…
Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
Giang Ngo, Dat Phan Trong, Dang Nguyen +2
Bayesian Optimization critically depends on the choice of acquisition function, but no single strategy is universally optimal; the best choice is non-stationary and problem-depende…