--- title: "Who cites Interpretable Long-Form Legal — 72 citing papers" description: "72 papers of the Elamur Research library cite «Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large…" canonical: "https://research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Interpretable Long-Form Legal Question Answering…](https://md.research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/) / cited by # Who cites «Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models» 72 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models»](https://md.research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/) 1. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 339 citations* 2. [**A Reasoning-Focused Legal Retrieval Benchmark arXiv:2505.03970**Lucia Zheng, Neel Guha, Javokhir Arifov, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-reasoning-focused-legal-retrieval-benchmark/) 3. **[LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English](https://md.research.elamur.ai/free/en/papers/s-2024-lexsumm-lext5-benchmarking-modeling-legal/) [Natural Legal Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/nllp/)**Santosh T.Y.S.S, Cornelius Weiss, Matthias Grabmair*2024 · 16 citations* 4. **[Explainability and Interpretability of Multilingual Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/resck-2025-explainability-interpretability-multilingual-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lucas Resck, Isabelle Augenstein, Anna Korhonen*2025 · 11 citations* 5. [**Bilingual BSARD: Extending Statutory Article Retrieval to Dutch Proceedings of the 1st Regulatory NLP Workshop (RegNLP 2025)**Ehsan Lotfi, Nikolay Banar, Nerses Yuzbashyan, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/lotfi-2025-bilingual-bsard-extending-statutory-article/) 6. **[LLM Agents in Law: Taxonomy, Applications, and Challenges](https://md.research.elamur.ai/free/en/papers/liu-2026-llm-agents-law-taxonomy-applications/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuang Liu, Ruijia Zhang, Ruoyun Ma, et al.*2026 · 4 citations* 7. **[JuriFindIT: an Italian legal retrieval dataset](https://md.research.elamur.ai/free/en/papers/noce-2026-jurifindit-italian-legal-retrieval-dataset/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Niko Dalla Noce, Davide Colla, Sina Farhang Doust, et al.*2026 · 3 citations* 8. **[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* 9. **[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* 10. [**ANNOTARES: A Dataset for Extracting Logical Structures from German Statutory Texts arXiv:2608.03898**Ronja Schwarz, Jannik Strotgen*2026*](https://md.research.elamur.ai/free/en/papers/schwarz-2026-annotares-dataset-extracting-logical-structures/) 11. **[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* 12. **[From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation](https://md.research.elamur.ai/free/en/papers/lu-2026-query-counsel-structured-reasoning-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingfei Lu, Yi Zhang, Mengjia Wu, et al.*2026* 60 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/louis-2023-interpretable-long-form-legal-question/) — Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models