Papers › RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions

RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions

31 Dec 2024arXiv:2501.00353archive 2025-07-28

Wanlong Liu, Junying Chen, Ke Ji, Li Zhou, Wenyu Chen, Benyou Wang

Retrieval-Augmented Generation (RAG) has emerged as a key paradigm for enhancing large language models (LLMs) by incorporating external knowledge. However, current RAG methods face two limitations: (1) they only cover limited RAG scenarios. (2) They suffer from limited task diversity due to the lack of a general RAG dataset. To address these limitations, we propose RAG-Instruct, a general method for synthesizing diverse and high-quality RAG instruction data based on any source corpus. Our approach leverages (1) five RAG paradigms, which encompass diverse query-document relationships, and (2) instruction simulation, which enhances instruction diversity and quality by utilizing the strengths of existing instruction datasets. Using this method, we construct a 40K instruction dataset from Wikipedia, comprehensively covering diverse RAG scenarios and tasks. Experiments demonstrate that RAG-Instruct effectively enhances LLMs' RAG capabilities, achieving strong zero-shot performance and significantly outperforming various RAG baselines across a diverse set of tasks. RAG-Instruct is publicly available at https://github.com/FreedomIntelligence/RAG-Instruct.

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call_gpt4_with_retry freedomintelligence/rag-instruct/data_gen/generate_data.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 277423b157f6182a · report
load_data freedomintelligence/rag-instruct/retrieval_lm/passage_retrieval.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 0c3de3890cd0b382 · report
load_items freedomintelligence/rag-instruct/retrieval_lm/passage_retrieval.py official repository ran · our draft was wrong Apache-2.0 (permissive) · c3045447a535da01 · report
process_item freedomintelligence/rag-instruct/retrieval_lm/passage_retrieval.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 0a08200e3e35e3bc · report
select_from_data freedomintelligence/rag-instruct/data_gen/generate_data.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 4dda4d8bdfbbf323 · report
table_to_csv_string freedomintelligence/rag-instruct/train_rag_sft.py official repository ran · our draft was wrong Apache-2.0 (permissive) · 4b9933d832571ead · report

Tasks

DiversityRAGRetrievalRetrieval-augmented Generation

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Methods

AdamAttentionAttention DropoutBARTBERTBPEDense ConnectionsDropoutLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionRAGResidual ConnectionSETSoftmaxWeight DecayWordPiece

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