🧑‍🔬 Who cites Qi Liu

238 citations of their works from 235 papers of our library (of the 141,840 whose bibliographies we read) · 27 with a page here, the most cited first · ← Qi Liu

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIIEEE Computer Society Conference on Computer Vision and Pattern RecognitionXiang Yue, Yuansheng Ni, Kai Zhang, et al.2023 · 948 citations
1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic CapabilitiesarXiv:2507.06261Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.2025 · 906 citations
   Mask-Predict: Parallel Decoding of Conditional Masked Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al.2019 · 671 citations
   How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source SuitesScience China Information SciencesZhe Chen, Weiyun Wang, Hao Tian, et al.2024 · 529 citations
2. Defending Against Neural Fake NewsarXiv:1905.12616Rowan Zellers, Ari Holtzman, Hannah Rashkin, et al.2019 · 466 citations
3. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 440 citations
   Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video AnalysisIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChaoyou Fu, Yuhan Dai, Yongdong Luo, et al.2024 · 404 citations
   MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 318 citations
4. 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 · 276 citations
5. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 267 citations
   FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative FlowConference on Empirical Methods in Natural Language Processing (EMNLP)Xuezhe Ma, Chunting Zhou, Xian Li, et al.2019 · 214 citations
   Logical Natural Language Generation from Open-Domain TablesAnnual Meeting of the Association for Computational Linguistics (ACL)Wenhu Chen, Jianshu Chen, Yu Su, et al.2020 · 209 citations
   Enabling Language Models to Fill in the BlanksAnnual Meeting of the Association for Computational Linguistics (ACL)Chris Donahue, Mina Lee, Percy Liang2020 · 207 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 · 173 citations
6. Efficient Training of Language Models to Fill in the MiddlearXiv:2207.14255Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.2022 · 138 citations
7. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 135 citations
8. Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine TranslationarXiv:2006.10369Jungo Kasai, Nikolaos Pappas, Hao Peng, et al.2020 · 132 citations
   Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Li, Yuqi Wang, Runxin Xu, et al.2024 · 123 citations
9. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
   LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 110 citations
   Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationIEEE Computer Society Conference on Computer Vision and Pattern RecognitionChengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.2024 · 100 citations
   Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language ModelsFindings of the Association for Computational LinguisticsWenhao Shi, Zhiqiang Hu, Yi Bin, et al.2024 · 86 citations
   AudioBench: A Universal Benchmark for Audio Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Xunlong Zou, Geyu Lin, et al.2025 · 75 citations
10. CogVLM2: Visual Language Models for Image and Video UnderstandingarXiv:2408.16500Wenyi Hong, Weihan Wang, Ming Ding, et al.2024 · 52 citations
    Scaling Laws and Compute-Optimal Training Beyond Fixed Training DurationsConference on Neural Information Processing Systems (NeurIPS)Alexander Hägele, Elie Bakouch, Atli Kosson, et al.2024 · 26 citations
11. Cutting Through the Noise: Boosting LLM Performance on Math Word ProblemsUjjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.2024 · 7 citations
    Multimodal LLMs Do Not Compose Skills Optimally across ModalitiesLanguage Resources and Evaluation Conference (LREC)Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune2026

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