---
title: "Who cites Sheng Wang — 131 papers of our library"
description: "131 papers of the Elamur Research library cite the works of Sheng Wang, found in their bibliographies; the most cited first."
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---
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# Who cites Sheng Wang

139 citations of their works from 131 papers of our library (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← Sheng Wang](https://md.research.elamur.ai/free/en/authors/sheng-wang/)

1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-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/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
2. **[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*
3. **[MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 554 citations*
4. **[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*
5. [**Multimodal Chain-of-Thought Reasoning in Language Models arXiv:2302.00923**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2023 · 308 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-multimodal-chain-thought-reasoning-language/)
6. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
7. **[An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-image-worth-1-2-tokens/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Liang Chen, Haozhe Zhao, Tianyu Liu, et al.*2024 · 279 citations*
8. [**Capabilities of Gemini Models in Medicine arXiv:2404.18416**Khaled Saab, Tao Tu, Wei-Hung Weng, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/saab-2024-capabilities-gemini-models-medicine/)
9. [**MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark arXiv:2409.02813**Xiang Yue, Tianyu Zheng, Yuansheng Ni, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-mmmu-pro-more-robust-multi/)
10. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
11. [**Med-Flamingo: a Multimodal Medical Few-shot Learner arXiv:2307.15189**Michael Moor, Qian Huang, Shirley Wu, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/moor-2023-med-flamingo-multimodal-medical-few/)
12. [**ChartLlama: A Multimodal LLM for Chart Understanding and Generation arXiv:2311.16483**Yucheng Han, Chi Zhang, Xin Chen, et al.*2023 · 99 citations*](https://md.research.elamur.ai/free/en/papers/han-2023-chartllama-multimodal-llm-chart-understanding/)
13. [**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/)
14. [**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/)
15. [**mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models arXiv:2408.04840**Jiabo Ye, Haiyang Xu, Haowei Liu, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-mplug-owl3-towards-long-image/)
16. **[mDPO: Conditional Preference Optimization for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-mdpo-conditional-preference-optimization-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fei Wang, Wenxuan Zhou, James Y. Huang, et al.*2024 · 50 citations*
17. [**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/)
18. **[CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-ccd-mitigating-hallucinations-radiology-mllms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Zhang, Zaiqiao Meng, Jake Lever, et al.*2026 · 2 citations*
19. **[LVLM-Aware Multimodal Retrieval for RAG-Based Medical Diagnosis with General-Purpose Models](https://md.research.elamur.ai/free/en/papers/mazor-2026-lvlm-aware-multimodal-retrieval-rag/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nir Mazor, Tom Hope*2026 · 2 citations*
20. **[Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations](https://md.research.elamur.ai/free/en/papers/xue-2026-enhancing-safety-medical-vision-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhiyu Xue, Reza Abbasi-Asl, Ramtin Pedarsani*2026 · 1 citation*
21. **[RA-RRG: Multimodal Retrieval-Augmented Radiology Report Generation with Key Phrase Extraction](https://md.research.elamur.ai/free/en/papers/park-2026-ra-rrg-multimodal-retrieval-augmented/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jonggwon Park, Byungmu Yoon, Soobum Kim, et al.*2026 · 1 citation*
22. **[Benchmarking and Mitigating the Impact of Noisy User Prompts in Medical VLMs via Cross-Modal Reflection](https://md.research.elamur.ai/free/en/papers/xue-2026-benchmarking-mitigating-impact-noisy-user/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhiyu Xue, Reza Abbasi-Asl, Ramtin Pedarsani*2026*
23. **[BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs](https://md.research.elamur.ai/free/en/papers/singha-2026-biovlm-routing-prompts-not-parameters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mainak Singha, Tanisha Gupta, Ankit Jha, et al.*2026*
24. **[MedKInstruct: A Multimodal Knowledge Graph Based Framework for Multi-Hop and Hard-Negative Instruction Data Synthesis in MedVQA](https://md.research.elamur.ai/free/en/papers/wu-2026-medkinstruct-multimodal-knowledge-graph-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinan Wu, Jihang Jin, Xuhao Bao, et al.*2026*
25. **[MENTOR: Efficient Autoregressive Image Generation with Balanced Multimodal Control](https://md.research.elamur.ai/free/en/papers/zhao-2026-mentor-efficient-autoregressive-image-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2026*
26. **[Position: Biomedical NLP Demands Specialization, Not Generalization](https://md.research.elamur.ai/free/en/papers/wasi-2026-position-biomedical-nlp-demands-specialization/) [Workshop on Linguistic Analysis for Health](https://md.research.elamur.ai/free/en/venues/healing/)**Toushik Wasi, Azmine*2026*
27. **[R³: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-r-3-end-end-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFei Wang, Qizhi Pei, Jiangtao Feng, et al.*2026*
28. **[ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vix-ray-vietnamese-chest-x/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duy Vu Minh Nguyen, Chinh Thanh Truong, Trần Hoàng Phúc, et al.*2026*
29. **[Why Multimodal In-Context Learning Lags Behind? Unveiling the Inner Mechanisms and Bottlenecks](https://md.research.elamur.ai/free/en/papers/wang-2026-why-multimodal-context-learning-lags/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Wang, Sharon Li*2026*

102 more citing papers of our library have no page here yet.

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