activity
20222026
most citedWhat Makes a Good Natural Language Prompt?

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Spectral-Aware Analytic Class-Incremental Learning for Long-Tailed Distributions

Quyen Tran, Hai Nguyen, Quan Dao +4

Analytic Continual Learning (ACL) offers a computationally efficient alternative to gradient-based approaches. Recent ACL methods are based on Recursive Least Squares (RLS) and hav…

cs.CL2025★ 1 cited

What Makes a Good Natural Language Prompt?

Do Xuan Long, Duy Dinh, Ngoc-Hai Nguyen +4

As large language models (LLMs) have progressed towards more human-like and human--AI communications have become prevalent, prompting has emerged as a decisive component. However,…

cs.LG2024

On Barycenter Computation: Semi-Unbalanced Optimal Transport-based Method on Gaussians

Ngoc-Hai Nguyen, Dung Le, Hoang-Phi Nguyen +2

We explore a robust version of the barycenter problem among centered Gaussian probability measures, termed Semi-Unbalanced Optimal Transport (SUOT)-based Barycenter, wherein th…

cs.CL2024

LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs

Do Xuan Long, Hai Nguyen Ngoc, Tiviatis Sim +5

We present the first systematic evaluation examining format bias in performance of large language models (LLMs). Our approach distinguishes between two categories of an evaluation…

cs.LG2022

An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning

Quyen Tran, Hai Nguyen, Hoang Phan +6

In online incremental learning, data continuously arrives with substantial distributional shifts, creating a significant challenge because previous samples have limited replay valu…