3 papers
cs.CL2025
FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation
Zhuocheng Zhang, Yang Feng, Min Zhang
Retrieval-Augmented Generation (RAG) plays a pivotal role in modern large language model applications, with numerous existing frameworks offering a wide range of functionalities to…
cs.CL2025
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searchers
Zhuocheng Zhang, Yang Feng, Min Zhang
Retrieval-Augmented Generation (RAG) is a crucial method for mitigating hallucinations in Large Language Models (LLMs) and integrating external knowledge into their responses. Exis…
cs.CL2023
Addressing the Length Bias Problem in Document-Level Neural Machine Translation
Zhuocheng Zhang, Shuhao Gu, Min Zhang +1
Document-level neural machine translation (DNMT) has shown promising results by incorporating more context information. However, this approach also introduces a length bias problem…