mlsanityData to 7 Oct 2026

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering

arXiv 2402.11129 ↗First posted 16 Feb 2024cs.CLcited by 29

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

Abstract (arXiv)

Retrieval-augmented Large Language Models (LLMs) offer substantial benefits in enhancing performance across knowledge-intensive scenarios. However, these methods often face challenges with complex inputs and encounter difficulties due to noisy knowledge retrieval, notably hindering model effectiveness. To address this issue, we introduce BlendFilter, a novel approach that elevates retrieval-augmented LLMs by integrating query generation blending with knowledge filtering. BlendFilter proposes the blending process through its query generation method, which integrates both external and internal knowledge augmentation with the original query, ensuring comprehensive information gathering. Additionally, our distinctive knowledge filtering module capitalizes on the intrinsic capabilities of the LLM, effectively eliminating extraneous data. We conduct extensive experiments on three open-domain question answering benchmarks, and the findings clearly indicate that our innovative BlendFilter surpasses state-of-the-art baselines significantly.

Key facts. Cited by 29 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 38 of its 53 references that are in the map. First posted on arXiv 16 Feb 2024.

Builds on

38 of 53 references.

Closest ancestors · 1

Same direction, newest first

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

Other references · 37

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  7. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  8. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,767
  9. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  10. 2023Qwen Technical Reportcited by 3,273
  11. 2022Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answeringcited by 1,881
  12. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
25 more
  1. 2020Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Stepscited by 1,259
  2. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  3. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,054
  4. 2023Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMscited by 946
  5. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 940
  6. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 911
  7. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 803
  8. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  9. 2021Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategiescited by 736
  10. 2023Active Retrieval Augmented Generationcited by 506
  11. 2021ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interactioncited by 464
  12. 2023Benchmarking Large Language Models for News Summarizationcited by 444
  13. 2023Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergycited by 343
  14. 2022Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPcited by 316
  15. 2023Query Rewriting for Retrieval-Augmented Large Language Modelscited by 211
  16. 2022Internet-augmented language models through few-shot prompting for open-domain question answeringcited by 131
  17. 2023Almanac: Retrieval-Augmented Language Models for Clinical Medicinecited by 122
  18. 2023Answering Questions by Meta-Reasoning over Multiple Chains of Thoughtcited by 87
  19. 2023Improving Language Models via Plug-and-Play Retrieval Feedbackcited by 87
  20. 2023Self-Knowledge Guided Retrieval Augmentation for Large Language Modelscited by 69
  21. 2023Are LLMs All You Need for Task-Oriented Dialogue?cited by 52
  22. 2023LLatrieval: LLM-Verified Retrieval for Verifiable Generationcited by 52
  23. 2023Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-agent LLMcited by 18
  24. 2023Zero-Shot Cross-Lingual Summarization via Large Language Modelscited by 16
  25. 2021Answering Open-Domain Multi-Answer Questions via a Recall-then-Verify Frameworkcited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 10; 2025: 17; 2026: 2.

29 papers.

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  1. 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 450
  2. 2024From Matching to Generation: A Survey on Generative Information Retrievalcited by 89
  3. 2024A Survey on Retrieval-Augmented Text Generation for Large Language Modelscited by 77
  4. 2024SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domainscited by 28
  5. 2025Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaborationcited by 19
  6. 2025Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuningcited by 17
  7. 2025Towards Omni-RAG: Comprehensive Retrieval-Augmented Generation for Large Language Models in Medical Applicationscited by 13
  8. 2024Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphscited by 10
  9. 2025LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searcherscited by 10
  10. 2025RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimizationcited by 9
  11. 2024A Hybrid RAG System with Comprehensive Enhancement on Complex Reasoningcited by 8
  12. 2024RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generationcited by 8
17 more
  1. 2024PEANuT: Parameter-Efficient Adaptation with Weight-aware Neural Tweakerscited by 8
  2. 2025Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editingcited by 6
  3. 2025REIS: A High-Performance and Energy-Efficient Retrieval System with In-Storage Processingcited by 4
  4. 2025CoCoA: Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergycited by 4
  5. 2024Augmenting Compliance-Guaranteed Customer Service Chatbots: Context-Aware Knowledge Expansion with Large Language Modelscited by 3
  6. 2025Bridging External and Parametric Knowledge: Mitigating Hallucination of LLMs with Shared-Private Semantic Synergy in Dual-Stream Knowledgecited by 3
  7. 2025RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentationcited by 3
  8. 2025Test-time Corpus Feedback: From Retrieval to RAGcited by 3
  9. 2025Exploring Reasoning-Infused Text Embedding with Large Language Models for Zero-Shot Dense Retrievalcited by 2
  10. 2024A Survey of Query Optimization in Large Language Modelscited by 1
  11. 2025Single LLM, Multiple Roles: A Unified Retrieval-Augmented Generation Framework Using Role-Specific Token Optimizationcited by 1
  12. 2025Beyond Independent Passages: Adaptive Passage Combination Retrieval for Retrieval Augmented Open-Domain Question Answeringcited by 1
  13. 2025Enhancing LLM Generation with Knowledge Hypergraph for Evidence-Based Medicinecited by 0
  14. 2025The Other Side of the Coin: Exploring Fairness in Retrieval-Augmented Generationcited by 0
  15. 2025In-Context Compositional Learning via Sparse Coding Transformercited by 0
  16. 2026RIMS: Preference Optimization via Smoothed Multi-pair Aggregation for Small-Scale LLM Retrieval-Augmented Generationcited by 0
  17. 2026Forgotten History or Test-of-Time? Retrospect and Prospect on RAG from an IR Perspectivecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026ReFilter: Improving Robustness of Retrieval-Augmented Generation via Gated Filter
  2. 2026Rethinking Retrieval-Augmentation as Synthesis: A Query-Aware Context Merging Approach
  3. 2024Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models
  4. 2024KBM: Delineating Knowledge Boundary for Adaptive Retrieval in Large Language Models
  5. 2024Retrieval-Augmented Generation for Natural Language Processing: A Survey
  6. 2025From Retrieval to Generation: Comparing Different Approaches
  7. 2024Reliable, Adaptable, and Attributable Language Models with Retrieval
  8. 2024REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering