--- title: "Who cites SlideVQA: A Dataset for — 53 citing papers" description: "53 papers of the Elamur Research library cite «SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images», found in their…" canonical: "https://research.elamur.ai/free/en/papers/tanaka-2023-slidevqa-dataset-document-visual-question/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/tanaka-2023-slidevqa-dataset-document-visual-question/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [SlideVQA: A Dataset for Document Visual Question…](https://md.research.elamur.ai/free/en/papers/tanaka-2023-slidevqa-dataset-document-visual-question/) / cited by # Who cites «SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images» 53 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images»](https://md.research.elamur.ai/free/en/papers/tanaka-2023-slidevqa-dataset-document-visual-question/) 1. **[MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations](https://md.research.elamur.ai/free/en/papers/ma-2024-mmlongbench-doc-benchmarking-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Ma, Yuhang Zang, Liangyu Chen, et al.*2024 · 92 citations* 2. **[Unifying Multimodal Retrieval via Document Screenshot Embedding](https://md.research.elamur.ai/free/en/papers/ma-2024-unifying-multimodal-retrieval-document-screenshot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.*2024 · 61 citations* 3. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/) 4. **[ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents](https://md.research.elamur.ai/free/en/papers/wang-2025-vidorag-visual-document-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qiuchen Wang, Ruixue Ding, Zehui Chen, et al.*2025 · 39 citations* 5. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/) 6. **[VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2025-vrag-rl-empower-vision-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Qiuchen Wang, Ruixue Ding, Yu Zeng, et al.*2025 · 23 citations* 7. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Navve Wasserman, Roi Pony, Oshri Naparstek, et al.*2025 · 22 citations* 8. **[M-LongDoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework](https://md.research.elamur.ai/free/en/papers/chia-2025-m-longdoc-benchmark-multimodal-super/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yew Ken Chia, Liying Cheng, Hou Pong Chan, et al.*2025 · 21 citations* 9. **[SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement](https://md.research.elamur.ai/free/en/papers/jain-2025-simpledoc-multi-modal-document-understanding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chelsi Jain, Yiran Wu, Yifan Zeng, et al.*2025 · 16 citations* 10. **[MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrieval](https://md.research.elamur.ai/free/en/papers/wu-2025-molorag-bootstrapping-document-understanding-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xixi Wu, Yanchao Tan, Nan Hou, et al.*2025 · 12 citations* 11. **[Doc-React: Multi-page Heterogeneous Document Question-answering](https://md.research.elamur.ai/free/en/papers/wu-2025-doc-react-multi-page-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junda Wu, Yu Xia, Tong Yu, et al.*2025 · 6 citations* 12. **[HybridKV: Hybrid KV Cache Compression for Efficient Multimodal Large Language Model Inference](https://md.research.elamur.ai/free/en/papers/zeng-2026-hybridkv-hybrid-kv-cache-compression/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowen Zeng, Feiyang Ren, Jun Zhang, et al.*2026 · 4 citations* 13. **[Evaluating Multimodal Large Language Models on Vertically Written Japanese Text](https://md.research.elamur.ai/free/en/papers/sasagawa-2026-evaluating-multimodal-large-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Keito Sasagawa, Shuhei Kurita, Daisuke Kawahara*2026 · 3 citations* 14. **[DocLens: A Tool-Augmented Multi-Agent Framework for Long Visual Document Understanding](https://md.research.elamur.ai/free/en/papers/zhu-2026-doclens-tool-augmented-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dawei Zhu, Rui Meng, Jiefeng Chen, et al.*2026 · 2 citations* 15. **[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* 16. **[ALDEN: Reinforcement Learning for Active Navigation and Evidence Gathering in Long Documents](https://md.research.elamur.ai/free/en/papers/yang-2026-alden-reinforcement-learning-active-navigation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Yang, Terry Ruas, Yijun Tian, et al.*2026* 17. **[Doc-V*: Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA](https://md.research.elamur.ai/free/en/papers/zheng-2026-doc-v-coarse-fine-interactive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanlei Zheng, Pei Fu, Hang Li, et al.*2026* 18. **[ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images](https://md.research.elamur.ai/free/en/papers/sibue-2026-exstructiny-benchmark-schema-variable-structured/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, et al.*2026* 19. **[Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains](https://md.research.elamur.ai/free/en/papers/xiong-2026-lang2act-fine-grained-visual-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqi Xiong, Chunyi Peng, Zhipeng Xu, et al.*2026* 20. **[MAB-DQA: Addressing Query Aspect Importance in Document Question Answering with Multi-Armed Bandits](https://md.research.elamur.ai/free/en/papers/xiang-2026-mab-dqa-addressing-query-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Xiang, Yunshan Ma, Xiaoyu Du, et al.*2026* 21. **[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* 32 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/tanaka-2023-slidevqa-dataset-document-visual-question/) — SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images