mlsanityData to 7 Oct 2026

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

arXiv 2404.04302 ↗First posted 4 Apr 2024cs.CL cs.AIcited by 70

On the map: LLM reasoning → Reasoning for agents, planning and code

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Abstract (arXiv)

Retrieval-Augmented Generation (RAG) enhances Large Language Model (LLM) output by providing prior knowledge as context to input. This is beneficial for knowledge-intensive and expert reliant tasks, including legal question-answering, which require evidence to validate generated text outputs. We highlight that Case-Based Reasoning (CBR) presents key opportunities to structure retrieval as part of the RAG process in an LLM. We introduce CBR-RAG, where CBR cycle's initial retrieval stage, its indexing vocabulary, and similarity knowledge containers are used to enhance LLM queries with contextually relevant cases. This integration augments the original LLM query, providing a richer prompt. We present an evaluation of CBR-RAG, and examine different representations (i.e. general and domain-specific embeddings) and methods of comparison (i.e. inter, intra and hybrid similarity) on the task of legal question-answering. Our results indicate that the context provided by CBR's case reuse enforces similarity between relevant components of the questions and the evidence base leading to significant improvements in the quality of generated answers.

Key facts. Cited by 70 papers in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 11 of its 24 references that are in the map. First posted on arXiv 4 Apr 2024.

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11 of 24 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models20 Aug

Other references · 10

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2023Mistral 7Bcited by 3,065
  5. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  6. 2021LexGLUE: A Benchmark Dataset for Legal Language Understanding in Englishcited by 302
  7. 2023Regulating ChatGPT and other Large Generative AI Modelscited by 102
  8. 2021Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented Dialogcited by 33
  9. 2023PolicyGPT: Automated Analysis of Privacy Policies with Large Language Modelscited by 16
  10. 2023LexGPT 0.1: pre-trained GPT-J models with Pile of Lawcited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 44; 2026: 20.

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  1. 2025BrowseComp-ZH: Benchmarking Web Browsing Ability of Large Language Models in Chinesecited by 139
  2. 2025Memento: Fine-tuning LLM Agents without Fine-tuning LLMscited by 119
  3. 2025RAG vs. GraphRAG: A Systematic Evaluation and Key Insightscited by 51
  4. 2025Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMscited by 40
  5. 2025The Homogenizing Effect of Large Language Models on Human Expression and Thoughtcited by 35
  6. 2025A Survey on Knowledge-Oriented Retrieval-Augmented Generationcited by 34
  7. 2025A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directionscited by 30
  8. 2025Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Surveycited by 29
  9. 2024Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation Systemscited by 26
  10. 2025Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settingscited by 22
  11. 2025AI Hiring with LLMs: A Context-Aware and Explainable Multi-Agent Framework for Resume Screeningcited by 19
  12. 2025Silent Leaks: Implicit Knowledge Extraction Attack on RAG Systems through Benign Queriescited by 19
38 more
  1. 2025CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Modelscited by 17
  2. 2024On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domainscited by 14
  3. 2025Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoningcited by 13
  4. 2025Review of Case-Based Reasoning for LLM Agents: Theoretical Foundations, Architectural Components, and Cognitive Integrationcited by 12
  5. 2025Towards Reliable Retrieval in RAG Systems for Large Legal Datasetscited by 12
  6. 2025Large Language Models Meet Legal Artificial Intelligence: A Surveycited by 9
  7. 2025Bridging Legal Knowledge and AI: Retrieval-Augmented Generation with Vector Stores, Knowledge Graphs, and Hierarchical Non-negative Matrix Factorizationcited by 8
  8. 2025Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approachcited by 6
  9. 2025NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law Systemcited by 5
  10. 2025Token-Level Precise Attack on RAG: Searching for the Best Alternatives to Mislead Generationcited by 5
  11. 2024Towards Retrieval Augmented Generation over Large Video Librariescited by 4
  12. 2025Towards Transparent RAG: Fostering Evidence Traceability in LLM Generation via Reinforcement Learningcited by 4
  13. 2025REIS: A High-Performance and Energy-Efficient Retrieval System with In-Storage Processingcited by 4
  14. 2025AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarioscited by 3
  15. 2025When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governancecited by 3
  16. 2024Quebec Automobile Insurance Question-Answering With Retrieval-Augmented Generationcited by 2
  17. 2025GAIus: Combining Genai with Legal Clauses Retrieval for Knowledge-based Assistantcited by 2
  18. 2025Universal Legal Article Prediction via Tight Collaboration between Supervised Classification Model and LLMcited by 2
  19. 2026Core-based Hierarchies for Efficient GraphRAGcited by 2
  20. 2026Fine-grained Claim-level RAG Benchmark for Lawcited by 2
  21. 2024Adversarial Databases Improve Success in Retrieval-based Large Language Modelscited by 1
  22. 2024A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinementcited by 1
  23. 2025Precise Legal Sentence Boundary Detection for Retrieval at Scale: NUPunkt and CharBoundarycited by 1
  24. 2025PAKTON: A Multi-Agent Framework for Question Answering in Long Legal Agreementscited by 1
  25. 2025KG2QA: Knowledge Graph-enhanced Retrieval-augmented Generation for Communication Standards Question Answeringcited by 1
  26. 2025TAI Scan Tool: A RAG-Based Tool With Minimalistic Input for Trustworthy AI Self-Assessmentcited by 1
  27. 2025Segment First, Retrieve Better: Realistic Legal Search via Rhetorical Role-Based Queriescited by 1
  28. 2025Build AI Assistants using Large Language Models and Agents to Enhance the Engineering Education of Biomechanicscited by 1
  29. 2025TagRAG: Tag-guided Hierarchical Knowledge Graph Retrieval-Augmented Generationcited by 1
  30. 2025Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVMcited by 0
  31. 2025D2S-FLOW: Automated Parameter Extraction from Datasheets for SPICE Model Generation Using Large Language Modelscited by 0
  32. 2025Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: A Comparative Studycited by 0
  33. 2025Memory-Driven Self-Improvement for Decision Making with Large Language Modelscited by 0
  34. 2025The 3rd Place Solution of CCIR CUP 2025: A Framework for Retrieval-Augmented Generation in Multi-Turn Legal Conversationcited by 0
  35. 2025Cognitive Alignment in Personality Reasoning: Leveraging Prototype Theory for MBTI Inferencecited by 0
  36. 2025Comparing the Performance of LLMs in RAG-based Question-Answering: A Case Study in Computer Science Literaturecited by 0
  37. 2025Sensorium Arc: AI Agent System for Oceanic Data Exploration and Interactive Eco-Artcited by 0
  38. 2025ArtistMus: A Globally Diverse, Artist-Centric Benchmark for Retrieval-Augmented Music Question Answeringcited by 0

50 most cited of 70 All 70 (JSON)

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  1. 2025A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications
  2. 2025All for law and law for all: Adaptive RAG Pipeline for Legal Research
  3. 2025Augmented Question-guided Retrieval (AQgR) of Indian Case Law with LLM, RAG, and Structured Summaries ↗
  4. 2025A Reasoning-Focused Legal Retrieval Benchmark
  5. 2025LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation
  6. 2026CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method
  7. 2024LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain
  8. 2026Legal-DC: Benchmarking Retrieval-Augmented Generation for Legal Documents