🧑‍🔬 Who cites Yiyang Zhou

391 citations of their works from 368 papers of our library (of the 149,439 whose bibliographies we read) · 86 with a page here, the most cited first · ← Yiyang Zhou

1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
2. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
3. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
4. Improved Baselines with Visual Instruction TuningIEEE Computer Society Conference on Computer Vision and Pattern RecognitionHaotian Liu, Chunyuan Li, Yuheng Li, et al.2023 · 2,614 citations
5. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
6. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
7. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
8. 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
9. 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
10. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
11. 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
12. MMBench: Is Your Multi-modal Model an All-around Player?Lecture notes in computer scienceYuan Liu, Haodong Duan, Yuanhan Zhang, et al.2023 · 942 citations
13. Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any ResolutionarXiv:2409.12191Peng Wang, Shuai Bai, Sinan Tan, et al.2024 · 860 citations
14. 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
15. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 468 citations
16. 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
17. ShareGPT4V: Improving Large Multi-Modal Models with Better CaptionsLecture notes in computer scienceLin Chen, Jinsong Li, Xiaoyi Dong, et al.2023 · 454 citations
18. VILA: On Pre-training for Visual Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJi Lin, Hongxu Yin, Wei Ping, et al.2023 · 381 citations
19. VideoChat: Chat-Centric Video UnderstandingScience China Information SciencesKunChang Li, Yinan He, Yi Wang, et al.2023 · 365 citations
20. MM-Vet: Evaluating Large Multimodal Models for Integrated CapabilitiesarXiv:2308.02490Weihao Yu, Zhengyuan Yang, Linjie Li, et al.2023 · 344 citations
21. HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
22. LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionarXiv:2303.16199Renrui Zhang, Jiaming Han, Chris Liu, et al.2023 · 333 citations
23. 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
24. The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)arXiv:2309.17421Zhengyuan Yang, Linjie Li, Kevin Lin, et al.2023 · 311 citations
25. OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsScience China Information SciencesYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 306 citations
26. Are We on the Right Way for Evaluating Large Vision-Language Models?Conference on Neural Information Processing Systems (NeurIPS)Lin Chen, Jinsong Li, Xiaoyi Dong, et al.2024 · 277 citations
27. SEED-Bench: Benchmarking Multimodal LLMs with Generative ComprehensionarXiv:2307.16125Bohao Li, Rui Wang, Guangzhi Wang, et al.2023 · 265 citations
28. InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
29. Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingarXiv:2306.02858Hang Zhang, Xin Li, Lidong Bing2023 · 238 citations
30. MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?Lecture notes in computer scienceRenrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.2024 · 232 citations
31. Shikra: Unleashing Multimodal LLM's Referential Dialogue MagicarXiv:2306.15195Keqin Chen, Zhao Zhang, Weili Zeng, et al.2023 · 210 citations
32. MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningarXiv:2310.09478Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.2023 · 199 citations
33. Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction TuningarXiv:2306.14565Fuxiao Liu, Kevin Lin, Linjie Li, et al.2023 · 189 citations
34. The False Promise of Imitating Proprietary LLMsarXiv:2305.15717Arnav Gudibande, Eric Wallace, Charlie Snell, et al.2023 · 182 citations
35. Aligning Large Multimodal Models with Factually Augmented RLHFarXiv:2309.14525Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.2023 · 176 citations
36. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 161 citations
37. SeeClick: Harnessing GUI Grounding for Advanced Visual GUI AgentsarXiv:2401.10935Kanzhi Cheng, Qiushi Sun, Yougang Chu, et al.2024 · 135 citations
38. UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language ModelFindings of the Association for Computational LinguisticsJiabo Ye, Anwen Hu, Haiyang Xu, et al.2023 · 129 citations
39. mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document UnderstandingFindings of the Association for Computational LinguisticsAnwen Hu, Haiyang Xu, Jiabo Ye, et al.2024 · 111 citations
40. Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?Conference on Empirical Methods in Natural Language Processing (EMNLP)Yang Chen, Hexiang Hu, Yi Luan, et al.2023 · 111 citations
41. 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
42. 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
43. 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
44. 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
45. MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction TuningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, et al.2024 · 86 citations
46. Factuality of Large Language Models: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor, et al.2024 · 77 citations
47. 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
48. Evaluation of OpenAI o1: Opportunities and Challenges of AGIarXiv:2409.18486Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.2024 · 64 citations
49. mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Anwen Hu, Haiyang Xu, Liang Zhang, et al.2025 · 62 citations
50. Multimodal Table UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Mingyu Zheng, Xinwei Feng, Qingyi Si, et al.2024 · 62 citations
51. MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language BenchmarkarXiv:2402.04788Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.2024 · 60 citations
52. MMICL: Empowering Vision-language Model with Multi-Modal In-Context LearningarXiv:2309.07915Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.2023 · 58 citations
53. 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
54. SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific GraphsarXiv:2308.03349Shengzhi Li, Nima Tajbakhsh2023 · 50 citations
55. Large Multilingual Models Pivot Zero-Shot Multimodal Learning across LanguagesarXiv:2308.12038Jinyi Hu, Yuan Yao, Chongyi Wang, et al.2023 · 43 citations
56. 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
57. InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug DiscoveryInternational Conference on Computational Linguistics (COLING)He Cao, Zijing Liu, Xingyu Lu, et al.2025 · 38 citations
58. Protecting Privacy in Multimodal Large Language Models with MLLMU-BenchConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Zheyuan Liu, Guangyao Dou, Mengzhao Jia, et al.2025 · 24 citations
59. Cracking the Code of Hallucination in LVLMs with Vision-aware Head DivergenceAnnual Meeting of the Association for Computational Linguistics (ACL)Jinghan He, Kuan Zhu, Haiyun Guo, et al.2025 · 21 citations
60. Shallow Focus, Deep Fixes: Enhancing Shallow Layers Vision Attention Sinks to Alleviate Hallucination in LVLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaofeng Zhang, Yihao Quan, Chen Shen, et al.2025 · 14 citations
61. Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QAConference of the European Chapter of the Association for Computational Linguistics (EACL)Jongwoo Park, Kanchana Ranasinghe, Kumara Kahatapitiya, et al.2026 · 13 citations
62. What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction TuningInternational Conference on Computational Linguistics (COLING)Yifan Du, Hangyu Guo, Kun Zhou, et al.2025 · 13 citations
63. CMM-Math: A Chinese Multimodal Math Dataset To Evaluate and Enhance the Mathematics Reasoning of Large Multimodal ModelsACM International Conference on Multimedia (ACM MM)Wentao Liu, Qianjun Pan, Yi Zhang, et al.2024 · 13 citations
64. Activation Steering Decoding: Mitigating Hallucination in Large Vision-Language Models through Bidirectional Hidden State InterventionAnnual Meeting of the Association for Computational Linguistics (ACL)Jingran Su, Jingfan Chen, Hongxin Li, et al.2025 · 12 citations
65. Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, et al.2025 · 12 citations
66. Can Multimodal Large Language Models Understand Spatial Relations?Annual Meeting of the Association for Computational Linguistics (ACL)Jingping Liu, Ziyan Liu, Zhedong Cen, et al.2025 · 11 citations
67. MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language ModelarXiv:2409.13729Zhen Yang, Jinhao Chen, Zhengxiao Du, et al.2024 · 10 citations
68. ViLBench: A Suite for Vision-Language Process Reward ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)Haoqin Tu, Weitao Feng, Hardy Chen, et al.2025 · 9 citations
69. Revealing and Enhancing Core Visual Regions: Harnessing Internal Attention Dynamics for Hallucination Mitigation in LVLMsFindings of the Association for Computational LinguisticsGuangtao Lyu, Qi Liu, Chenghao Xu, et al.2026 · 5 citations
70. RRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human FeedbackInternational Conference on Computational Linguistics (COLING)Guoqing Chen, Fu Zhang, Jinghao Lin, et al.2025 · 5 citations
71. Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Shunqi Mao, Chaoyi Zhang, Weidong Cai2026 · 4 citations
72. SynthRL: Scaling Visual Reasoning with Verifiable Data SynthesisFindings of the Association for Computational LinguisticsZijian Wu, Jinjie Ni, Xiangyan Liu, et al.2026 · 3 citations
73. VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information BottleneckAnnual Meeting of the Association for Computational Linguistics (ACL)Feiran Zhang, Yixin Wu, Zhenghua Wang, et al.2026 · 3 citations
74. BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Bryan Chen Zhengyu Tan, Weihua Zheng, Zhengyuan Liu, et al.2026 · 2 citations
75. PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMsFindings of the Association for Computational LinguisticsZijing Wang, YongKang Liu, Mingyang Wang, et al.2026 · 1 citation
76. Vision-Language Introspection: Mitigating Overconfident Hallucinations in MLLMs via Interpretable Bi-Causal SteeringAnnual Meeting of the Association for Computational Linguistics (ACL)Shuliang Liu, Songbo Yang, Dong Fang, et al.2026 · 1 citation
77. Ask Me Again Differently: GRAS for Measuring Bias in Vision Language Models on Gender, Race, Age, and Skin ToneFindings of the Association for Computational LinguisticsShaivi Malik, Hasnat Md Abdullah, Sriparna Saha, et al.2026
78. CEBC: Conformal Evidence-Bounded Control for Low-Hallucination Vision–Language GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Ashish Mishra, Tarun Kumar, Arpit Shah, et al.2026
79. Faithful Medical Dialogue Generation Using Homo-Heterogeneous Exemplar-based In-Context Knowledge GroundingLanguage Resources and Evaluation Conference (LREC)Priyanshu Priya, Hardik Goyal, Asif Ekbal2026
80. Journey Before Destination: On the importance of Visual Faithfulness in Slow ThinkingConference of the European Chapter of the Association for Computational Linguistics (EACL)Rheeya Uppaal, Phu Mon Htut, Min Bai, et al.2026
81. KCVR: Knowledge-Centric Video Reconstruction for Structured Pedagogical Summarization via Dynamic Graph PlanningAnnual Meeting of the Association for Computational Linguistics (ACL)Jingjiang Liu, Jia Zhu, Hanghui Guo, et al.2026
82. 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
83. Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual EnhancementAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenxin Qin, Qiang Li, Qingzhuo Wang, et al.2026
84. Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool CompositionAnnual Meeting of the Association for Computational Linguistics (ACL)Ye Wang, Qianglong Chen, Siyuan Wang, et al.2026
85. Thinking Like a Botanist: Challenging Multimodal Language Models with Intent Driven Chain-of-InquiryFindings of the Association for Computational LinguisticsSyed Nazmus Sakib, Nafiul Haque, Shahrear Bin Amin, et al.2026
86. VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-EvaluationFindings of the Association for Computational LinguisticsSeongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.2026

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