---
title: "Who cites REAL-MM-RAG: A Real-World — 17 citing papers"
description: "17 papers of the Elamur Research library cite «REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/wasserman-2025-real-mm-rag-real-world/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [REAL-MM-RAG: A Real-World Multi-Modal Retrieval…](https://md.research.elamur.ai/free/en/papers/wasserman-2025-real-mm-rag-real-world/) / cited by

# Who cites «REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark»

17 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark»](https://md.research.elamur.ai/free/en/papers/wasserman-2025-real-mm-rag-real-world/)

1. **[ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios](https://md.research.elamur.ai/free/en/papers/loison-2026-vidore-v3-comprehensive-evaluation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**António Loison, Quentin Macé, Antoine Edy, et al.*2026 · 7 citations*
2. **[Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework](https://md.research.elamur.ai/free/en/papers/yan-2026-sculpting-vector-space-efficient-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Mingdong Ou, Yi Cao, et al.*2026 · 2 citations*
3. **[Agentic Oversight via Dialectic Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2026-agentic-oversight-dialectic-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Federico Ranaldi*2026*
4. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026*
5. **[MDocRAG-RL: Empowering Multi-Modal Document RAG via Complex Visual Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-mdocrag-rl-empowering-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongyu Wang*2026*
6. **[Take It All: Ensemble Retrieval for Multimodal Evidence Aggregation](https://md.research.elamur.ai/free/en/papers/upravitelev-2026-take-it-all-ensemble-retrieval/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Max Upravitelev, Veronika Solopova, Premtim Sahitaj, et al.*2026*

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

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