6 papers
Latent Abstraction for Retrieval-Augmented Generation
Ha Lan N. T, Minh-Anh Nguyen, Dung D. Le
Retrieval-Augmented Generation (RAG) has become a standard approach for enhancing large language models (LLMs) with external knowledge, mitigating hallucinations, and improving fac…
Tracing the Evolution of Word Embedding Techniques in Natural Language Processing
Minh Anh Nguyen, Kuheli Sai, Minh Nguyen
This work traces the evolution of word-embedding techniques within the natural language processing (NLP) literature. We collect and analyze 149 research articles spanning the perio…
VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models
Nguyen Tien Dong, Minh-Anh Nguyen, Thanh Dat Hoang +6
The rapid advancement of large language models (LLMs) has enabled new possibilities for applying artificial intelligence within the legal domain. Nonetheless, the complexity, hiera…
VoteGCL: Enhancing Graph-based Recommendations with Majority-Voting LLM-Rerank Augmentation
Minh-Anh Nguyen, Bao Nguyen, Ha Lan N. T. +3
Recommendation systems often suffer from data sparsity caused by limited user-item interactions, which degrade their performance and amplify popularity bias in real-world scenarios…
JEPA4Rec: Learning Effective Language Representations for Sequential Recommendation via Joint Embedding Predictive Architecture
Minh-Anh Nguyen, Dung D. Le
Language representation learning has emerged as a promising approach for sequential recommendation, thanks to its ability to learn generalizable representations. However, despite i…
One STEP at a time: Language Agents are Stepwise Planners
Minh Nguyen, Ehsan Shareghi
Language agents have shown promising adaptability in dynamic environments to perform complex tasks. However, despite the versatile knowledge embedded in large language models, thes…