3 papers
cs.CL2026
DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation
Rui Chu, Bingyin Zhao, Thanh Quoc Hung Le +6
Large language models (LLMs) have achieved unprecedented success due to their exceptional generative capabilities. However, because they depend on knowledge encapsulated from train…
cs.LG2025
MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMs
Quang H. Nguyen, Thinh Dao, Duy C. Hoang +4
The rapid progress in machine learning (ML) has brought forth many large language models (LLMs) that excel in various tasks and areas. These LLMs come with different abilities and…
cs.LG2025
Momentum Contrastive Learning with Enhanced Negative Sampling and Hard Negative Filtering
Duy Hoang, Huy Ngo, Khoi Pham +3
Contrastive learning has become pivotal in unsupervised representation learning, with frameworks like Momentum Contrast (MoCo) effectively utilizing large negative sample sets to e…