🧑‍🔬 Who cites Liangyu Chen

153 citations of their works from 153 papers of our library (of the 149,439 whose bibliographies we read) · 39 with a page here, the most cited first · ← Liangyu Chen

1. 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 · 1,005 citations
2. Evaluating Object Hallucination in Large Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Yifan Li, Yifan Du, Kun Zhou, et al.2023 · 1,004 citations
3. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
4. Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and BeyondarXiv:2308.12966Jinze Bai, Shuai Bai, Shusheng Yang, et al.2023 · 970 citations
5. Video-LLaVA: Learning United Visual Representation by Alignment Before ProjectionConference on Empirical Methods in Natural Language Processing (EMNLP)Bin Lin, Yang Ye, Bin Zhu, et al.2023 · 628 citations
6. MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.2023 · 554 citations
7. 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 · 541 citations
8. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
9. MVBench: A Comprehensive Multi-modal Video Understanding BenchmarkIEEE Computer Society Conference on Computer Vision and Pattern RecognitionKunchang Li, Yali Wang, Yinan He, et al.2023 · 463 citations
10. ShareGPT4V: Improving Large Multi-Modal Models with Better CaptionsLecture notes in computer scienceLin Chen, Jinsong Li, Xiaoyi Dong, et al.2023 · 454 citations
11. InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic TasksarXiv:2312.14238Zhe Chen, Jiannan Wu, Wenhai Wang, et al.2023 · 435 citations
12. MM-Vet: Evaluating Large Multimodal Models for Integrated CapabilitiesarXiv:2308.02490Weihao Yu, Zhengyuan Yang, Linjie Li, et al.2023 · 344 citations
13. LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionarXiv:2303.16199Renrui Zhang, Jiaming Han, Chris Liu, et al.2023 · 333 citations
14. MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
15. SEED-Bench: Benchmarking Multimodal LLMs with Generative ComprehensionarXiv:2307.16125Bohao Li, Rui Wang, Guangzhi Wang, et al.2023 · 265 citations
16. InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
17. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingarXiv:2306.02858Hang Zhang, Xin Li, Lidong Bing2023 · 238 citations
18. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
19. Shikra: Unleashing Multimodal LLM's Referential Dialogue MagicarXiv:2306.15195Keqin Chen, Zhao Zhang, Weili Zeng, et al.2023 · 210 citations
20. Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction TuningarXiv:2306.14565Fuxiao Liu, Kevin Lin, Linjie Li, et al.2023 · 189 citations
21. Aligning Large Multimodal Models with Factually Augmented RLHFarXiv:2309.14525Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.2023 · 176 citations
22. SeeClick: Harnessing GUI Grounding for Advanced Visual GUI AgentsarXiv:2401.10935Kanzhi Cheng, Qiushi Sun, Yougang Chu, et al.2024 · 135 citations
23. 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 · 115 citations
24. InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large ModelarXiv:2401.16420Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 94 citations
25. InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and CompositionarXiv:2309.15112Pan Zhang, Xiaoyi Dong, Bin Wang, et al.2023 · 87 citations
26. Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text IntegrationarXiv:2306.09093Chenyang Lyu, Minghao Wu, Longyue Wang, et al.2023 · 75 citations
27. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 70 citations
28. Investigating the Catastrophic Forgetting in Multimodal Large Language ModelsarXiv:2309.10313Yuexiang Zhai, Shengbang Tong, Xiao Li, et al.2023 · 59 citations
29. MMICL: Empowering Vision-language Model with Multi-Modal In-Context LearningarXiv:2309.07915Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.2023 · 58 citations
30. InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HDConference on Neural Information Processing Systems (NeurIPS)Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 54 citations
31. InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and OutputarXiv:2407.03320Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.2024 · 39 citations
32. Peacock: A Family of Arabic Multimodal Large Language Models and BenchmarksAnnual Meeting of the Association for Computational Linguistics (ACL)Fakhraddin Alwajih, El Moatez Billah Nagoudi, Gagan Bhatia, et al.2024 · 28 citations
33. M-LongDoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning FrameworkConference on Empirical Methods in Natural Language Processing (EMNLP)Yew Ken Chia, Liying Cheng, Hou Pong Chan, et al.2025 · 21 citations
34. MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought VerificationAnnual Meeting of the Association for Computational Linguistics (ACL)Linzhuang Sun, Hao Liang, Jingxuan Wei, et al.2025 · 19 citations
35. Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language ModelsarXiv:2312.01714Bingshuai Liu, Chenyang Lyu, Zijun Min, et al.2023 · 13 citations
36. Aquila2 Technical ReportarXiv:2408.07410Bo-Wen Zhang, Liangdong Wang, Jijie Li, et al.2024 · 1 citation
37. Latent Attention Denoising: A Training-Free Energy-Based Framework for Mitigating Hallucinations in Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiwen Luo, Siyu Jiang, Weilong Jiang, et al.2026
38. SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating ProceduresFindings of the Association for Computational LinguisticsJiaming Wang, Zhe Tang, Zehao Jin, et al.2026
39. Why Multimodal In-Context Learning Lags Behind? Unveiling the Inner Mechanisms and BottlenecksAnnual Meeting of the Association for Computational Linguistics (ACL)Yu Wang, Sharon Li2026

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