---
title: "Who cites CoIR: A Comprehensive — 22 citing papers"
description: "22 papers of the Elamur Research library cite «CoIR: A Comprehensive Benchmark for Code Information Retrieval Models», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/li-2025-coir-comprehensive-benchmark-code-information/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/li-2025-coir-comprehensive-benchmark-code-information/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [CoIR: A Comprehensive Benchmark for Code…](https://md.research.elamur.ai/free/en/papers/li-2025-coir-comprehensive-benchmark-code-information/) / cited by

# Who cites «CoIR: A Comprehensive Benchmark for Code Information Retrieval Models»

22 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «CoIR: A Comprehensive Benchmark for Code Information Retrieval Models»](https://md.research.elamur.ai/free/en/papers/li-2025-coir-comprehensive-benchmark-code-information/)

1. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
2. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
3. **[Tailoring Memory Granularity for Multi-Hop Reasoning over Long Contexts](https://md.research.elamur.ai/free/en/papers/qing-2026-tailoring-memory-granularity-multi-hop/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peijun Qing, Xingjian Diao, Chiyu Ma, et al.*2026 · 3 citations*
4. **[More Than Efficiency: Embedding Compression Improves Domain Adaptation in Dense Retrieval](https://md.research.elamur.ai/free/en/papers/zuo-2026-more-than-efficiency-embedding-compression/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Chunsheng Zuo, Daniel Khashabi*2026 · 2 citations*
5. **[A Survey of Reasoning-Intensive Retrieval: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/wei-2026-survey-reasoning-intensive-retrieval-progress/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyang Wei, Tingyu Song, Siyue Zhang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/li-2025-coir-comprehensive-benchmark-code-information/) — CoIR: A Comprehensive Benchmark for Code Information Retrieval Models