---
title: "Who cites Reliable, Adaptable, and — 39 citing papers"
description: "39 papers of the Elamur Research library cite «Reliable, Adaptable, and Attributable Language Models with Retrieval», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/asai-2024-reliable-adaptable-attributable-language-models/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/asai-2024-reliable-adaptable-attributable-language-models/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reliable, Adaptable, and Attributable Language…](https://md.research.elamur.ai/free/en/papers/asai-2024-reliable-adaptable-attributable-language-models/) / cited by

# Who cites «Reliable, Adaptable, and Attributable Language Models with Retrieval»

39 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «Reliable, Adaptable, and Attributable Language Models with Retrieval»](https://md.research.elamur.ai/free/en/papers/asai-2024-reliable-adaptable-attributable-language-models/)

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
2. [**Fine-grained Hallucination Detection and Editing for Language Models arXiv:2401.06855**Abhika Mishra, Akari Asai, Vidhisha Balachandran, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2024-fine-grained-hallucination-detection-editing/)
3. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/)
4. [**Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens arXiv:2401.17377**Jiacheng Liu, Sewon Min, Luke Zettlemoyer, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-infini-gram-scaling-unbounded-n/)
5. **[RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework](https://md.research.elamur.ai/free/en/papers/zhu-2025-rageval-scenario-specific-rag-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kunlun Zhu, Yifan Luo, Dingling Xu, et al.*2025 · 34 citations*
6. **[VISA: Retrieval Augmented Generation with Visual Source Attribution](https://md.research.elamur.ai/free/en/papers/ma-2025-visa-retrieval-augmented-generation-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Shengyao Zhuang, Bevan Koopman, et al.*2025 · 22 citations*
7. **[RaDeR: Reasoning-aware Dense Retrieval Models](https://md.research.elamur.ai/free/en/papers/das-2025-rader-reasoning-aware-dense-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Debrup Das, Sam O'Nuallain, Razieh Rahimi*2025 · 14 citations*
8. **[Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization](https://md.research.elamur.ai/free/en/papers/huang-2025-improving-contextual-faithfulness-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Huang, Xiaocheng Feng, Weitao Ma, et al.*2025 · 11 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/asai-2024-reliable-adaptable-attributable-language-models/) — Reliable, Adaptable, and Attributable Language Models with Retrieval