---
title: "Who cites SaulLM-7B: A pioneering Large — 101 citing papers"
description: "101 papers of the Elamur Research library cite «SaulLM-7B: A pioneering Large Language Model for Law», found in their bibliographies; the…"
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---
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# Who cites «SaulLM-7B: A pioneering Large Language Model for Law»

101 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «SaulLM-7B: A pioneering Large Language Model for Law»](https://md.research.elamur.ai/free/en/papers/colombo-2024-saullm-7b-pioneering-large-language/)

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. [**InternLM-Law: An Open Source Chinese Legal Large Language Model arXiv:2406.14887**Zhiwei Fei, Songyang Zhang, Xiaoyu Shen, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/fei-2024-internlm-law-open-source/)
3. **[RedOne 2.0: Rethinking Domain-specific LLM Post-Training in Social Networking Services](https://md.research.elamur.ai/free/en/papers/zhao-2026-redone-2-0-rethinking-domain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fei zhao, Chonggang Lu, Haofu Qian, et al.*2026 · 2 citations*
4. **[Robust Uncertainty Quantification for Self-Evolving Large Language Models via Continual Domain Pretraining](https://md.research.elamur.ai/free/en/papers/zhou-2026-robust-uncertainty-quantification-self-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaofan Zhou, Lu Cheng*2026 · 2 citations*
5. **[QuALA-NL: Question & Answer with Legal Attribution in Dutch](https://md.research.elamur.ai/free/en/papers/drie-2026-quala-nl-question-answer-legal/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Romy A.N. van Drie, Roos M. Bakker, Daan L. Di Scala, et al.*2026 · 1 citation*
6. **[AYN: A Tiny Yet Competitive Indian Legal Language Model Pretrained from Scratch](https://md.research.elamur.ai/free/en/papers/niyogi-2026-ayn-tiny-yet-competitive-indian/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026*
7. **[Compressing Language Models for Specialized Domains](https://md.research.elamur.ai/free/en/papers/williams-2026-compressing-language-models-specialized-domains/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Miles Williams, George Chrysostomou, Vitor Amancio Jeronymo, et al.*2026*
8. [**GradeLegal: Automated Grading for German Legal Cases arXiv:2605.21076**Abdullah Al Zubaer, Lorenz Wendlinger, Simon Alexander Nonn, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zubaer-2026-gradelegal-automated-grading-german-legal/)
9. **[Is Micro Domain-Adaptive Pre-Training Effective for Real-World Operations? Multi-Step Evaluation Reveals Potential and Bottlenecks](https://md.research.elamur.ai/free/en/papers/tsunokake-2026-is-micro-domain-adaptive-pre/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Masaya Tsunokake, Yuta Koreeda, Terufumi Morishita, et al.*2026*
10. **[Pub-LawBench: Public-Oriented Benchmarking for LegalAI](https://md.research.elamur.ai/free/en/papers/zheng-2026-pub-lawbench-public-oriented-benchmarking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiaoyu Zheng, Zehan Ma, Yijing Zhang, et al.*2026*
11. **[ViLegalLM: Language Models for Vietnamese Legal Text](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vilegallm-language-models-vietnamese-legal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Truong-Phuc Nguyen, Quy-Nhan Nguyen, Minh-Tien Nguyen*2026*

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

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