mlsanityData to 7 Oct 2026

LocalRQA: From Generating Data to Locally Training, Testing, and Deploying Retrieval-Augmented QA Systems

arXiv 2403.00982 ↗First posted 1 Mar 2024cs.CLcited by 7

On the map: Retrieval-augmented generation → RAG robustness and adaptive retrieval

Abstract (arXiv)

Retrieval-augmented question-answering systems combine retrieval techniques with large language models to provide answers that are more accurate and informative. Many existing toolkits allow users to quickly build such systems using off-the-shelf models, but they fall short in supporting researchers and developers to customize the model training, testing, and deployment process. We propose LocalRQA, an open-source toolkit that features a wide selection of model training algorithms, evaluation methods, and deployment tools curated from the latest research. As a showcase, we build QA systems using online documentation obtained from Databricks and Faire's websites. We find 7B-models trained and deployed using LocalRQA reach a similar performance compared to using OpenAI's text-ada-002 and GPT-4-turbo.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in RAG robustness and adaptive retrieval, one of 15 directions in Retrieval-augmented generation. Builds on 25 of its 47 references that are in the map. First posted on arXiv 1 Mar 2024.

Builds on

25 of 47 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection17 Oct

Other references · 24

  1. 2022Training language models to follow instructions with human feedbackcited by 15,712
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  5. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
  6. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  7. 2017TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehensioncited by 2,895
  8. 2017Billion-scale similarity search with GPUscited by 2,477
  9. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,205
  10. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  11. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  12. 2020RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Modelscited by 1,235
12 more
  1. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,225
  2. 2022Text Embeddings by Weakly-Supervised Contrastive Pre-trainingcited by 1,216
  3. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  4. 2021Unsupervised Dense Information Retrieval with Contrastive Learningcited by 1,203
  5. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  6. 2020Distilling Knowledge from Reader to Retriever for Question Answeringcited by 226
  7. 2019Gradio: Hassle-Free Sharing and Testing of ML Models in the Wildcited by 176
  8. 2022Training Language Models with Memory Augmentationcited by 112
  9. 2022SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrievalcited by 90
  10. 2021Shades of BLEU, Flavours of Success: The Case of MultiWOZcited by 48
  11. 2016Revisiting Summarization Evaluation for Scientific Articlescited by 31
  12. 2023Robust Safety Classifier for Large Language Models: Adversarial Prompt Shieldcited by 24

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 3; 2026: 1.

7 papers.

  1. 2024FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Researchcited by 165
  2. 2025Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generationcited by 13
  3. 2024RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generationcited by 8
  4. 2025UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generationcited by 6
  5. 2024XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generationcited by 3
  6. 2025FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generationcited by 2
  7. 2026Improving Answer Extraction in Context-based Question Answering Systems Using LLMscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026LakeQA: An Exploratory QA Benchmark over a Million-Scale Data Lake
  2. 2022Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering
  3. 2024Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
  4. 2024RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering
  5. 2025SUNAR: Semantic Uncertainty based Neighborhood Aware Retrieval for Complex QA
  6. 2023PRCA: Fitting Black-Box Large Language Models for Retrieval Question Answering via Pluggable Reward-Driven Contextual Adapter
  7. 2025Efficient Context Selection for Long-Context QA: No Tuning, No Iteration, Just Adaptive-k
  8. 2025Improving Context Fidelity via Native Retrieval-Augmented Reasoning