---
title: "Who cites MegaPairs: Massive Data — 16 citing papers"
description: "16 papers of the Elamur Research library cite «MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [MegaPairs: Massive Data Synthesis for Universal…](https://md.research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/) / cited by

# Who cites «MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval»

16 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval»](https://md.research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/)

1. **[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*
2. **[DRAGON: Domain-specific Robust Automatic Data Generation for RAG Optimization](https://md.research.elamur.ai/free/en/papers/shen-2026-dragon-domain-specific-robust-automatic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyang Shen, Hang Yan, Zhongshi Xing, et al.*2026 · 1 citation*
3. **[Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/luo-2026-utility-oriented-visual-evidence-selection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiqing Luo, Zongye Hu, Xiao Wang, et al.*2026 · 1 citation*
4. **[AFMRL: Attribute-Enhanced Fine-Grained Multi-Modal Representation Learning in E-commerce](https://md.research.elamur.ai/free/en/papers/zhang-2026-afmrl-attribute-enhanced-fine-grained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Biao Zhang, Lixin Chen, Bin Zhang, et al.*2026*
5. **[Benchmarking the Fine-Grained Discriminability in Image-Text Retrieval via Controlled Contrastive Differences](https://md.research.elamur.ai/free/en/papers/wang-2026-benchmarking-fine-grained-discriminability-image/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Wang, Xi Zhou, Yating Yang, et al.*2026*
6. **[Beyond Query Bias: Candidate-Aware Iterative Refinement for Zero-Shot Composed Image Retrieval](https://md.research.elamur.ai/free/en/papers/sun-2026-beyond-query-bias-candidate-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nan Sun, Jing Tang, Lei Sun, et al.*2026*
7. **[Chart-MRAG: Benchmarking Multimodal Retrieval Augmented Generation on Chart-based Documents](https://md.research.elamur.ai/free/en/papers/ymyang-2026-chart-mrag-benchmarking-multimodal-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ymyang, Jiang Zhong, Li Jin, et al.*2026*
8. **[Knowledge Poisoning Attacks on Medical Multi-Modal Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/yang-2026-knowledge-poisoning-attacks-medical-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiru Yang, Haoran Zheng, Tong Ju, et al.*2026*
9. **[Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing](https://md.research.elamur.ai/free/en/papers/song-2026-rethinking-composed-image-retrieval-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tingyu Song, Yanzhao Zhang, Mingxin Li, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/) — MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval