---
title: "Who cites Yiyang Zhou — 368 papers of our library"
description: "368 papers of the Elamur Research library cite the works of Yiyang Zhou, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yiyang-zhou/cited-by/"
---
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# 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](https://md.research.elamur.ai/free/en/authors/yiyang-zhou/)

1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
3. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
4. **[Improved Baselines with Visual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,614 citations*
5. [**Qwen Technical Report arXiv:2309.16609**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,669 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
6. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
7. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning arXiv:2305.06500**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,100 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/)
8. **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 1,005 citations*
9. **[Evaluating Object Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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 Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
11. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond arXiv:2308.12966**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 970 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
12. **[MMBench: Is Your Multi-modal Model an All-around Player?](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 942 citations*
13. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution arXiv:2409.12191**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 860 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
14. **[Video-LLaVA: Learning United Visual Representation by Alignment Before Projection](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 628 citations*
15. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts arXiv:2310.02255**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 468 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
16. **[MVBench: A Comprehensive Multi-modal Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 463 citations*
17. **[ShareGPT4V: Improving Large Multi-Modal Models with Better Captions](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 454 citations*
18. **[VILA: On Pre-training for Visual Language Models](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 381 citations*
19. **[VideoChat: Chat-Centric Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2023-videochat-chat-centric-video-understanding/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**KunChang Li, Yinan He, Yi Wang, et al.*2023 · 365 citations*
20. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
21. **[HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 335 citations*
22. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention arXiv:2303.16199**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
23. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
24. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
25. **[OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 306 citations*
26. **[Are We on the Right Way for Evaluating Large Vision-Language Models?](https://md.research.elamur.ai/free/en/papers/chen-2024-right-way-evaluating-large-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2024 · 277 citations*
27. [**SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension arXiv:2307.16125**Bohao Li, Rui Wang, Guangzhi Wang, et al.*2023 · 265 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-seed-bench-benchmarking-multimodal-llms/)
28. **[InternVideo2: Scaling Foundation Models for Multimodal Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-internvideo2-scaling-foundation-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yi Wang, Kunchang Li, Xinhao Li, et al.*2024 · 253 citations*
29. [**Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding arXiv:2306.02858**Hang Zhang, Xin Li, Lidong Bing*2023 · 238 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-video-llama-instruction-tuned-audio/)
30. **[MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?](https://md.research.elamur.ai/free/en/papers/zhang-2024-mathverse-multi-modal-llm-truly/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Renrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.*2024 · 232 citations*
31. [**Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic arXiv:2306.15195**Keqin Chen, Zhao Zhang, Weili Zeng, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-shikra-unleashing-multimodal-llm-s/)
32. [**MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning arXiv:2310.09478**Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-minigpt-v2-large-language-model/)
33. [**Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning arXiv:2306.14565**Fuxiao Liu, Kevin Lin, Linjie Li, et al.*2023 · 189 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mitigating-hallucination-large-multi-modal/)
34. [**The False Promise of Imitating Proprietary LLMs arXiv:2305.15717**Arnav Gudibande, Eric Wallace, Charlie Snell, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/gudibande-2023-false-promise-imitating-proprietary-llms/)
35. [**Aligning Large Multimodal Models with Factually Augmented RLHF arXiv:2309.14525**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 176 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
36. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations*
37. [**SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents arXiv:2401.10935**Kanzhi Cheng, Qiushi Sun, Yougang Chu, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-seeclick-harnessing-gui-grounding-advanced/)
38. **[UReader: Universal OCR-free Visually-situated Language Understanding with Multimodal Large Language Model](https://md.research.elamur.ai/free/en/papers/ye-2023-ureader-universal-ocr-free-visually/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiabo Ye, Anwen Hu, Haiyang Xu, et al.*2023 · 129 citations*
39. **[mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2024-mplug-docowl-1-5-unified/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anwen Hu, Haiyang Xu, Jiabo Ye, et al.*2024 · 111 citations*
40. **[Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?](https://md.research.elamur.ai/free/en/papers/chen-2023-can-pre-trained-vision-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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 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*
42. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
43. [**InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition arXiv:2309.15112**Pan Zhang, Xiaoyi Dong, Bin Wang, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-internlm-xcomposer-vision-language/)
44. **[Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2024-math-llava-bootstrapping-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Shi, Zhiqiang Hu, Yi Bin, et al.*2024 · 86 citations*
45. **[MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2024-mmc-advancing-multimodal-chart-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, et al.*2024 · 86 citations*
46. **[Factuality of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2024-factuality-large-language-models-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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 Integration arXiv:2306.09093**Chenyang Lyu, Minghao Wu, Longyue Wang, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/lyu-2023-macaw-llm-multi-modal-language/)
48. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)
49. **[mPLUG-DocOwl2: High-resolution Compressing for OCR-free Multi-page Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2025-mplug-docowl2-high-resolution-compressing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anwen Hu, Haiyang Xu, Liang Zhang, et al.*2025 · 62 citations*
50. **[Multimodal Table Understanding](https://md.research.elamur.ai/free/en/papers/zheng-2024-multimodal-table-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Benchmark arXiv:2402.04788**Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mllm-judge-assessing-multimodal-llm/)
52. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/)
53. **[InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-4khd-pioneering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 54 citations*
54. [**SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs arXiv:2308.03349**Shengzhi Li, Nima Tajbakhsh*2023 · 50 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-scigraphqa-large-scale-synthetic-multi/)
55. [**Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages arXiv:2308.12038**Jinyi Hu, Yuan Yao, Chongyi Wang, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-large-multilingual-models-pivot-zero/)
56. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
57. **[InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery](https://md.research.elamur.ai/free/en/papers/cao-2025-instructmol-multi-modal-integration-building/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**He Cao, Zijing Liu, Xingyu Lu, et al.*2025 · 38 citations*
58. **[Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench](https://md.research.elamur.ai/free/en/papers/liu-2025-protecting-privacy-multimodal-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zheyuan Liu, Guangyao Dou, Mengzhao Jia, et al.*2025 · 24 citations*
59. **[Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence](https://md.research.elamur.ai/free/en/papers/he-2025-cracking-code-hallucination-lvlms-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 LVLMs](https://md.research.elamur.ai/free/en/papers/zhang-2025-shallow-focus-deep-fixes-enhancing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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 QA](https://md.research.elamur.ai/free/en/papers/park-2026-too-many-frames-not-all/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/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 Tuning](https://md.research.elamur.ai/free/en/papers/du-2025-what-makes-good-visual-instructions/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/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 Models](https://md.research.elamur.ai/free/en/papers/liu-2024-cmm-math-chinese-multimodal-math/) [ACM International Conference on Multimedia (ACM MM)](https://md.research.elamur.ai/free/en/venues/acm-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 Intervention](https://md.research.elamur.ai/free/en/papers/su-2025-activation-steering-decoding-mitigating-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingran Su, Jingfan Chen, Hongxin Li, et al.*2025 · 12 citations*
65. **[Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-modality-aware-neuron-pruning-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, et al.*2025 · 12 citations*
66. **[Can Multimodal Large Language Models Understand Spatial Relations?](https://md.research.elamur.ai/free/en/papers/liu-2025-can-multimodal-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingping Liu, Ziyan Liu, Zhedong Cen, et al.*2025 · 11 citations*
67. [**MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model arXiv:2409.13729**Zhen Yang, Jinhao Chen, Zhengxiao Du, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-mathglm-vision-solving-mathematical-problems/)
68. **[ViLBench: A Suite for Vision-Language Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/tu-2025-vilbench-suite-vision-language-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/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 LVLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-revealing-enhancing-core-visual-regions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangtao 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 Feedback](https://md.research.elamur.ai/free/en/papers/chen-2025-rrhf-v-ranking-responses-mitigate/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Guoqing Chen, Fu Zhang, Jinghao Lin, et al.*2025 · 5 citations*
71. **[Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM Decoding](https://md.research.elamur.ai/free/en/papers/mao-2026-through-magnifying-glass-adaptive-perception/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shunqi Mao, Chaoyi Zhang, Weidong Cai*2026 · 4 citations*
72. **[SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis](https://md.research.elamur.ai/free/en/papers/wu-2026-synthrl-scaling-visual-reasoning-verifiable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijian Wu, Jinjie Ni, Xiangyan Liu, et al.*2026 · 3 citations*
73. **[VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck](https://md.research.elamur.ai/free/en/papers/zhang-2026-vib-probe-detecting-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiran Zhang, Yixin Wu, Zhenghua Wang, et al.*2026 · 3 citations*
74. **[BLEnD-Vis: Benchmarking Multimodal Cultural Understanding in Vision Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-blend-vis-benchmarking-multimodal-cultural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/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 MLLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plam-training-free-plateau-guided/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijing Wang, YongKang Liu, Mingyang Wang, et al.*2026 · 1 citation*
76. **[Vision-Language Introspection: Mitigating Overconfident Hallucinations in MLLMs via Interpretable Bi-Causal Steering](https://md.research.elamur.ai/free/en/papers/liu-2026-vision-language-introspection-mitigating-overconfident/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Tone](https://md.research.elamur.ai/free/en/papers/malik-2026-ask-me-again-differently-gras/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaivi Malik, Hasnat Md Abdullah, Sriparna Saha, et al.*2026*
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81. **[KCVR: Knowledge-Centric Video Reconstruction for Structured Pedagogical Summarization via Dynamic Graph Planning](https://md.research.elamur.ai/free/en/papers/liu-2026-kcvr-knowledge-centric-video-reconstruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Models](https://md.research.elamur.ai/free/en/papers/luo-2026-latent-attention-denoising-training-free/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiwen Luo, Siyu Jiang, Weilong Jiang, et al.*2026*
83. **[Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual Enhancement](https://md.research.elamur.ai/free/en/papers/qin-2026-mitigating-action-relation-hallucinations-lvlms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenxin Qin, Qiang Li, Qingzhuo Wang, et al.*2026*
84. **[Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool Composition](https://md.research.elamur.ai/free/en/papers/wang-2026-simple-vgc-enhancing-visual-grounding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ye Wang, Qianglong Chen, Siyuan Wang, et al.*2026*
85. **[Thinking Like a Botanist: Challenging Multimodal Language Models with Intent Driven Chain-of-Inquiry](https://md.research.elamur.ai/free/en/papers/sakib-2026-thinking-like-botanist-challenging-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Syed Nazmus Sakib, Nafiul Haque, Shahrear Bin Amin, et al.*2026*
86. **[VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation](https://md.research.elamur.ai/free/en/papers/park-2026-vauq-vision-aware-uncertainty-quantification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.*2026*

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