---
title: "Who cites LegalBench-RAG: A Benchmark — 72 citing papers"
description: "72 papers of the Elamur Research library cite «LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain»…"
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---
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# Who cites «LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain»

72 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain»](https://md.research.elamur.ai/free/en/papers/pipitone-2024-legalbench-rag-benchmark-retrieval-augmented/)

1. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
2. **[Towards Knowledge Checking in Retrieval-augmented Generation: A Representation Perspective](https://md.research.elamur.ai/free/en/papers/zeng-2025-knowledge-checking-retrieval-augmented-generation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shenglai Zeng, Jiankun Zhang, Bingheng Li, et al.*2025 · 14 citations*
3. [**MizanQA: Benchmarking Large Language Models on Moroccan Legal Question Answering arXiv:2508.16357**Adil Bahaj, Mounir Ghogho*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/bahaj-2025-mizanqa-benchmarking-large-language-models/)
4. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
5. [**BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law arXiv:2605.28183**Sebastian Nagl, Ann-Kristin Mayrhofer, Martin Heidebach, et al.*2026*](https://md.research.elamur.ai/free/en/papers/nagl-2026-benger-benchmarking-llm-systems-subsumption/)
6. **[bLLeQA: Benchmarking LLMs for Grounded Legal Question-Answering in French and Dutch](https://md.research.elamur.ai/free/en/papers/banar-2026-blleqa-benchmarking-llms-grounded-legal/) [Workshop on Towards Knowledgeable Foundation Models](https://md.research.elamur.ai/free/en/venues/knowfm/)**Nikolay Banar, Ehsan Lotfi, Jens Van Nooten, et al.*2026*
7. **[MizanQA: A Benchmark for Multi-Answer Moroccan Legal QA](https://md.research.elamur.ai/free/en/papers/bahaj-2026-mizanqa-benchmark-multi-answer-moroccan/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Adil Bahaj, Mounir Ghogho*2026*

65 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/pipitone-2024-legalbench-rag-benchmark-retrieval-augmented/) — LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain