---
title: "Who cites BAMBOO: A Comprehensive — 53 citing papers"
description: "53 papers of the Elamur Research library cite «BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of…"
canonical: "https://research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/cited-by/"
---
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# Who cites «BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models»

53 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models»](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/)

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 · 3,222 citations*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
3. [**RULER: What's the Real Context Size of Your Long-Context Language Models? arXiv:2404.06654**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 386 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
4. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks arXiv:2412.15204**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 130 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/)
5. **[Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA](https://md.research.elamur.ai/free/en/papers/wang-2024-leave-no-document-behind-benchmarking/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minzheng Wang, Longze Chen, Fu Cheng, et al.*2024 · 71 citations*
6. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
7. [**Beyond Fluency: A Rubric-Based Benchmark for Evaluating Saudi Dialect and Cultural Competence in Large Language Models arXiv:2608.29990**Ghassan Al-Sumaidaee, Sajjad Abdoli, Ahmed Rashad, et al.*2026*](https://md.research.elamur.ai/free/en/papers/al-sumaidaee-2026-fluency-rubric-based-benchmark-evaluating/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/) — BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models