53 citations · 80 across the 10 of their papers we have counts for
10 papers
Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI
Hieu Man, Van-Cuong Pham, Nghia Trung Ngo +2
Learning robust representations of authorial style is crucial for authorship attribution and AI-generated text detection. However, existing methods often struggle with content-styl…
mSCoRe: a ultilingual and Scalable Benchmark for kill-based mmonsense asoning
Nghia Trung Ngo, Franck Dernoncourt, Thien Huu Nguyen
Recent advancements in reasoning-reinforced Large Language Models (LLMs) have shown remarkable capabilities in complex reasoning tasks. However, the mechanism underlying their util…
LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models
Hieu Man, Nghia Trung Ngo, Viet Dac Lai +3
Recent advancements in large language models (LLMs) based embedding models have established new state-of-the-art benchmarks for text embedding tasks, particularly in dense vector-b…
Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
Nghia Trung Ngo, Chien Van Nguyen, Franck Dernoncourt +1
Retrieval-augmented generation (RAG) has emerged as a promising approach to enhance the performance of large language models (LLMs) in knowledge-intensive tasks such as those from…
Zero-shot Cross-lingual Transfer Learning with Multiple Source and Target Languages for Information Extraction: Language Selection and Adversarial Training
Nghia Trung Ngo, Thien Huu Nguyen
The majority of previous researches addressing multi-lingual IE are limited to zero-shot cross-lingual single-transfer (one-to-one) setting, with high-resource languages predominan…
ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning
Hieu Man, Nghia Trung Ngo, Franck Dernoncourt +1
Large Language Models (LLMs) excel in various natural language processing tasks, but leveraging them for dense passage embedding remains challenging. This is due to their causal at…