--- title: "Who cites OBELICS: An Open Web-Scale Filtered Dataset of…" description: "113 papers of the Elamur Research library cite «OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents», found in their…" canonical: "https://research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [OBELICS: An Open Web-Scale Filtered Dataset of…](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/) / cited by # Who cites «OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents» 113 papers of our library cite it (of the 140,884 whose bibliographies we read) · 16 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/) 1. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/) 2. [**MMBench: Is Your Multi-modal Model an All-around Player?**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 907 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/) 3. [**Video-LLaVA: Learning United Visual Representation by Alignment Before Projection**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 614 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/) 4. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/) 5. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 413 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/) 6. [**Qwen3-VL Technical Report**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 330 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/) 7. [**OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) 8. [**GAIA: a benchmark for General AI Assistants**Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-gaia-benchmark-general-ai-assistants/) 9. [**What matters when building vision-language models?**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) 10. [**Aligning Large Multimodal Models with Factually Augmented RLHF**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/) 11. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/) 12. [**Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) 13. [**Chameleon: Mixed-Modal Early-Fusion Foundation Models**Chameleon Team*2024 · 117 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-chameleon-mixed-modal-early-fusion/) 14. [**Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data**Badr AlKhamissi, Yingtian Tang, Abdülkadir Gökce, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-dreaming-out-loud-self-synthesis/) 15. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/) 16. [**Wasm: A Pipeline for Constructing Structured Arabic Interleaved Multimodal Corpora**Khalil Hennara; Ahmad Bastati; Muhammad Hreden; Mohamed Motasim Hamed; Zeina Aldallal; Sara Chrouf;, Safwan AlModhayan*2025*](https://md.research.elamur.ai/free/en/papers/hennara-2025-wasm-pipeline-constructing-structured-arabic/) 97 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/) — OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents