3 papers
cs.IR2026
HaS: Accelerating RAG through Homology-Aware Speculative Retrieval
Peng Peng, Weiwei Lin, Wentai Wu +2
Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as context. However, retrieval bec…
cs.CL2025
Are We on the Right Way for Assessing Document Retrieval-Augmented Generation?
Wenxuan Shen, Mingjia Wang, Yaochen Wang +4
Retrieval-Augmented Generation (RAG) systems using Multimodal Large Language Models (MLLMs) show great promise for complex document understanding, yet their development is critical…
cs.CL2025
CrowdSelect: Synthetic Instruction Data Selection with Multi-LLM Wisdom
Yisen Li, Lingfeng Yang, Wenxuan Shen +4
Distilling advanced Large Language Models' instruction-following capabilities into smaller models using a selected subset has become a mainstream approach in model training. While…