---
title: "Who cites Xingyu Fu — 139 papers of our library"
description: "139 papers of the Elamur Research library cite the works of Xingyu Fu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/xingyu-fu/cited-by/"
---
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# Who cites Xingyu Fu

139 citations of their works from 139 papers of our library (of the 149,439 whose bibliographies we read) · 42 with a page here, the most cited first · [← Xingyu Fu](https://md.research.elamur.ai/free/en/authors/xingyu-fu/)

1. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arXiv:2403.05530**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
2. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone arXiv:2404.14219**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,134 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
3. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
4. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
5. [**Qwen3-VL Technical Report arXiv:2511.21631**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 370 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/)
6. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
7. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
8. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
9. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
10. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
11. [**LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models arXiv:2407.07895**Feng Li, Renrui Zhang, Hao Zhang, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-next-interleave-tackling-multi/)
12. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
13. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
14. [**GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning arXiv:2507.01006**GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-v-glm-4-5v-glm/)
15. **[MANTIS: Interleaved Multi-Image Instruction Tuning](https://md.research.elamur.ai/free/en/papers/jiang-2024-mantis-interleaved-multi-image-instruction/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Dongfu Jiang, Xuan He, Huaye Zeng, et al.*2024 · 74 citations*
16. [**Kimi-VL Technical Report arXiv:2504.07491**Kimi Team, Angang Du, Bohong Yin, et al.*2025 · 70 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-vl-technical-report/)
17. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
18. [**MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark arXiv:2410.19168**S Sakshi, Utkarsh Tyagi, Sonal Kumar, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/sakshi-2024-mmau-massive-multi-task-audio/)
19. [**Kimi K2.5: Visual Agentic Intelligence arXiv:2602.02276**Kimi Team, Tongtong Bai, Yifan Bai, et al.*2026 · 66 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2026-kimi-k2-5-visual/)
20. [**mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models arXiv:2408.04840**Jiabo Ye, Haiyang Xu, Haowei Liu, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-mplug-owl3-towards-long-image/)
21. [**MiMo-VL Technical Report arXiv:2506.03569**Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-vl-technical-report/)
22. **[CAMEL-Bench: A Comprehensive Arabic LMM Benchmark](https://md.research.elamur.ai/free/en/papers/ghaboura-2025-camel-bench-comprehensive-arabic-lmm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sara Ghaboura, Ahmed Heakl, Omkar Thawakar, et al.*2025 · 22 citations*
23. **[Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-multimodal-needle-haystack-benchmarking-long/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hengyi Wang, Haizhou Shi, Shiwei Tan, et al.*2025 · 21 citations*
24. **[What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations](https://md.research.elamur.ai/free/en/papers/liu-2025-what-is-that-talk-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongqi Liu, Chenxi Whitehouse, Xi Yu, et al.*2025 · 13 citations*
25. [**On the Importance of Tokenization in Arabic Embedding Models**Mohamed Alkaoud, Mairaj Syed*2020 · 11 citations*](https://md.research.elamur.ai/free/en/papers/alkaoud-2020-importance-tokenization-arabic-embedding-models/)
26. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations*
27. **[Cross-lingual transfer for low-resource Arabic language understanding](https://md.research.elamur.ai/free/en/papers/abboud-2022-cross-lingual-transfer-low-resource/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Khadige Abboud, Olga Golovneva, Christopher DiPersio*2022 · 8 citations*
28. [**ERNIE 5.0 Technical Report arXiv:2602.04705**Haifeng Wang, Hua Wu, Tian Wu, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2026-ernie-5-0-technical/)
29. **[DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings](https://md.research.elamur.ai/free/en/papers/mageed-2021-dialex-benchmark-evaluating-multidialectal-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Muhammad Abdul-Mageed, Shady Elbassuoni, Jad Doughman, et al.*2021 · 3 citations*
30. [**STEP3-VL-10B Technical Report arXiv:2601.09668**Ailin Huang, Chengyuan Yao, Chunrui Han, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)
31. **[From Pixels to BFS: High Maze Accuracy Does Not Imply Visual Planning](https://md.research.elamur.ai/free/en/papers/salgado-2026-pixels-bfs-high-maze-accuracy/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Rodriguez Salgado, Alberto Gonzalo*2026 · 1 citation*
32. **[RotBench: Evaluating Multi-modal Large Language Models on Identifying Image Rotation](https://md.research.elamur.ai/free/en/papers/niu-2026-rotbench-evaluating-multi-modal-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, et al.*2026 · 1 citation*
33. **[Visually-Guided Policy Optimization for Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-visually-guided-policy-optimization-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zengbin Wang, Feng Xiong, Liang Lin, et al.*2026 · 1 citation*
34. **[When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias](https://md.research.elamur.ai/free/en/papers/zou-2026-when-vision-language-models-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh, et al.*2026 · 1 citation*
35. **[ARM2: Adaptive Reasoning Model with Vision Understanding and Executable Code](https://md.research.elamur.ai/free/en/papers/xie-2026-arm2-adaptive-reasoning-model-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Xie, Zhendong Chu, Aoxiao Zhong, et al.*2026*
36. **[Cross-Modal Taxonomic Generalization in (Vision-) Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-cross-modal-taxonomic-generalization-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyang Xu, Marcelo Sandoval-Castañeda, Karen Livescu, et al.*2026*
37. **[Evaluating Discriminability of Vision-Language Models](https://md.research.elamur.ai/free/en/papers/muraoka-2026-evaluating-discriminability-vision-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Masayasu Muraoka, Naoaki Okazaki*2026*
38. **[From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception](https://md.research.elamur.ai/free/en/papers/zhu-2026-attenuation-attention-variational-information-flow/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jilong Zhu, Yang Feng*2026*
39. **[Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/sinha-2026-mind-s-eye-benchmark-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rohit Sinha, Aditya Sanjiv Kanade, Sai Srinivas Kancheti, et al.*2026*
40. **[S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language Models](https://md.research.elamur.ai/free/en/papers/shukla-2026-s2h-dpo-hardness-aware-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nitish Shukla, Surgan Jandial, Arun Ross*2026*
41. **[Seeing the Other Side: Diagnostic Tasks for Viewpoint Reasoning in Vision–Language Models](https://md.research.elamur.ai/free/en/papers/takenaka-2026-seeing-other-side-diagnostic-tasks/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Makoto Takenaka, Hitomi Yanaka*2026*
42. [**Semitic Root Encoding: Tokenization Based on the Templatic Morphology of Semitic Languages in NMT**Brendan T. Hatch, Stephen D. Richardson*2025*](https://md.research.elamur.ai/free/en/papers/hatch-2025-semitic-root-encoding-tokenization-based/)

97 more citing papers of our library have no page here yet.

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