Who cites «BLINK: Multimodal Large Language Models Can See but Not Perceive»
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
- Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,134 citations
- Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
- LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
- Qwen3-VL Technical ReportarXiv:2511.21631Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.2025 · 370 citations
- Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
- InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
- Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
- InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
- Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
- LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal ModelsarXiv:2407.07895Feng Li, Renrui Zhang, Hao Zhang, et al.2024 · 127 citations
- MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding BenchmarkarXiv:2409.02813Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.2024 · 123 citations
- A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
- GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement LearningarXiv:2507.01006GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.2025 · 89 citations
- MANTIS: Interleaved Multi-Image Instruction TuningTransactions on Machine Learning ResearchDongfu Jiang, Xuan He, Huaye Zeng, et al.2024 · 74 citations
- Kimi-VL Technical ReportarXiv:2504.07491Kimi Team, Angang Du, Bohong Yin, et al.2025 · 70 citations
- Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
- MMAU: A Massive Multi-Task Audio Understanding and Reasoning BenchmarkarXiv:2410.19168S Sakshi, Utkarsh Tyagi, Sonal Kumar, et al.2024 · 67 citations
- Kimi K2.5: Visual Agentic IntelligencearXiv:2602.02276Kimi Team, Tongtong Bai, Yifan Bai, et al.2026 · 66 citations
- mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language ModelsarXiv:2408.04840Jiabo Ye, Haiyang Xu, Haowei Liu, et al.2024 · 60 citations
- MiMo-VL Technical ReportarXiv:2506.03569Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.2025 · 33 citations
- CAMEL-Bench: A Comprehensive Arabic LMM BenchmarkFindings of the Association for Computational LinguisticsSara Ghaboura, Ahmed Heakl, Omkar Thawakar, et al.2025 · 22 citations
- Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hengyi Wang, Haizhou Shi, Shiwei Tan, et al.2025 · 21 citations
- What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific PresentationsAnnual Meeting of the Association for Computational Linguistics (ACL)Dongqi Liu, Chenxi Whitehouse, Xi Yu, et al.2025 · 13 citations
- TemplateRL: Structured Template-Guided Reinforcement Learning for LLM ReasoningFindings of the Association for Computational LinguisticsJinyang Wu, Chonghua Liao, Mingkuan Feng, et al.2026 · 8 citations
- ERNIE 5.0 Technical ReportarXiv:2602.04705Haifeng Wang, Hua Wu, Tian Wu, et al.2026 · 7 citations
- STEP3-VL-10B Technical ReportarXiv:2601.09668Ailin Huang, Chengyuan Yao, Chunrui Han, et al.2026 · 2 citations
- From Pixels to BFS: High Maze Accuracy Does Not Imply Visual PlanningWorkshop on Advances in Language and Vision Research (ALVR)Rodriguez Salgado, Alberto Gonzalo2026 · 1 citation
- RotBench: Evaluating Multi-modal Large Language Models on Identifying Image RotationConference of the European Chapter of the Association for Computational Linguistics (EACL)Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, et al.2026 · 1 citation
- Visually-Guided Policy Optimization for Multimodal ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Zengbin Wang, Feng Xiong, Liang Lin, et al.2026 · 1 citation
- When Vision-Language Models Judge Without Seeing: Exposing Informativeness BiasAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh, et al.2026 · 1 citation
- ARM2: Adaptive Reasoning Model with Vision Understanding and Executable CodeFindings of the Association for Computational LinguisticsJian Xie, Zhendong Chu, Aoxiao Zhong, et al.2026
- Cross-Modal Taxonomic Generalization in (Vision-) Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyang Xu, Marcelo Sandoval-Castañeda, Karen Livescu, et al.2026
- Evaluating Discriminability of Vision-Language ModelsLanguage Resources and Evaluation Conference (LREC)Masayasu Muraoka, Naoaki Okazaki2026
- Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Rohit Sinha, Aditya Sanjiv Kanade, Sai Srinivas Kancheti, et al.2026
- S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language ModelsFindings of the Association for Computational LinguisticsNitish Shukla, Surgan Jandial, Arun Ross2026
This page in Markdown → https://md.research.elamur.ai/free/en/papers/fu-2024-blink-multimodal-large-language-models/cited-by/