---
title: "Who cites LawBench: Benchmarking Legal Knowledge of Large…"
description: "164 papers of the Elamur Research library cite «LawBench: Benchmarking Legal Knowledge of Large Language Models», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [LawBench: Benchmarking Legal Knowledge of Large…](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/) / cited by

# Who cites «LawBench: Benchmarking Legal Knowledge of Large Language Models»

164 papers of our library cite it (of the 140,884 whose bibliographies we read) · 7 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)

1. [**Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models**Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.*2024 · 431 citations*](https://md.research.elamur.ai/free/en/papers/dahl-2024-large-legal-fictions-profiling-legal/)
2. [**Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture**Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-chatlaw-multi-agent-legal-assistant/)
3. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
4. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
5. [**Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models**Yeeun Kim, Youngrok Choi, Eunkyung Choi, et al.*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-developing-pragmatic-benchmark-assessing-korean/)
6. [**MizanQA: Benchmarking Large Language Models on Moroccan Legal Question Answering**Adil Bahaj, Mounir Ghogho*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/bahaj-2025-mizanqa-benchmarking-large-language-models/)
7. [**CLASE: A Hybrid Method for Chinese Legalese Stylistic Evaluation**Yiran Rex Ma, Yuxiao Ye, Huiyuan Xie*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ma-2026-clase-hybrid-method-chinese-legalese/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/) — LawBench: Benchmarking Legal Knowledge of Large Language Models