3 papers
cs.CR2026
Retrieved But Not Reliable: A Survey on Attacks, and Defenses in Retrieval-Augmented Generation
Minh Tran, Cuong Dang, Tuc Nguyen +10
Retrieval-Augmented Generation (RAG) enhances large language models by grounding outputs in external knowledge, improving factuality and reducing hallucinations. At the same time,…
cs.CL2026
How Robust Are LLMs to Vietnamese Dialects?
Minh Tran, Trinh Chau, Thanh-Nhan Le +4
Large Language Models (LLMs) are typically evaluated on standard written Vietnamese, yet everyday communication frequently involves regional dialects that preserve meaning but diff…
cs.CL2026
URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models
Vinh Nguyen, Cuong Dang, Jiahao Zhang +6
Retrieval-Augmented Generation (RAG) has emerged as a widely adopted approach for enhancing LLMs in scenarios that demand extensive factual knowledge. However, current RAG evaluati…