dongguanting/RAG-QA-40K

🔥Toward General Instruction-Following Alignment for Retrieval-Augmented Generation

🤖️ Website • 🤗 VIF-RAG-QA-110K • 👉 VIF-RAG-QA-20K • 📖 Arxiv • 🤗 HF-Paper

We propose a instruction-following alignement pipline named VIF-RAG framework and auto-evaluation Benchmark named FollowRAG:

• IF-RAG: It is the first automated, scalable, and verifiable data synthesis pipeline for aligning complex instruction-following in RAG scenarios. VIF-RAG integrates a verification process at each step of data augmentation and combination. We begin by manually creating a minimal set of atomic instructions (<100) and then apply steps including instruction composition, quality verification, instruction-query combination, and dual-stage verification to generate a large-scale, high-quality VIF-RAG-QA dataset (>100K).

• FollowRAG: To address the gap in instruction-following auto-evaluation for RAG systems, we introduce FollowRAG Benchmark, which includes approximately 3K test samples, covering 22 categories of general instruction constraints and 4 knowledge-intensive QA datasets. Due to its robust pipeline design, FollowRAG can seamlessly integrate with different RAG benchmarks

🎖 Citation

Please star our github repo and cite our work if you find the repository helpful.

@article{dong2024general,
  author       = {Guanting Dong and
                  Xiaoshuai Song and
                  Yutao Zhu and
                  Runqi Qiao and
                  Zhicheng Dou and
                  Ji{-}Rong Wen},
  title        = {Toward General Instruction-Following Alignment for Retrieval-Augmented
                  Generation},
  journal      = {CoRR},
  volume       = {abs/2410.09584},
  year         = {2024},
  url          = {https://doi.org/10.48550/arXiv.2410.09584},
  doi          = {10.48550/ARXIV.2410.09584},
  eprinttype    = {arXiv},
  eprint       = {2410.09584},
  timestamp    = {Fri, 22 Nov 2024 21:38:25 +0100},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2410-09584.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}}