---
title: "Who cites Bin Zhu — 204 papers of our library — Elamur Research"
description: "204 papers of the Elamur Research library cite the works of Bin Zhu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/bin-zhu/cited-by/"
---
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# Who cites Bin Zhu

204 citations of their works from 204 papers of our library (of the 149,439 whose bibliographies we read) · 44 with a page here, the most cited first · [← Bin Zhu](https://md.research.elamur.ai/free/en/authors/bin-zhu/)

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. [**Gemini: A Family of Highly Capable Multimodal Models arXiv:2312.11805**Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.*2023 · 3,050 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)
3. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
4. **[Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/) [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/)**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 427 citations*
5. **[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*
6. [**NExT-GPT: Any-to-Any Multimodal LLM arXiv:2309.05519**Shengqiong Wu, Hao Fei, Leigang Qu, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-next-gpt-any-any-multimodal/)
7. **[LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding](https://md.research.elamur.ai/free/en/papers/wu-2024-longvideobench-benchmark-long-context-interleaved/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Haoning Wu, Dongxu Li, Bei Chen, et al.*2024 · 166 citations*
8. **[MLVU: Benchmarking Multi-task Long Video Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2024-mlvu-benchmarking-multi-task-long/) [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/)**Junjie Zhou, Yan Shu, Bo Zhao, et al.*2024 · 140 citations*
9. [**LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models arXiv:2407.07895**Feng Li, Renrui Zhang, Hao Zhang, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-next-interleave-tackling-multi/)
10. [**VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs arXiv:2406.07476**Zesen Cheng, Sicong Leng, Hang Zhang, et al.*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-videollama-2-advancing-spatial-temporal/)
11. [**DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads arXiv:2410.10819**Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-duoattention-efficient-long-context-llm/)
12. [**A Survey on Hallucination in Large Vision-Language Models arXiv:2402.00253**Hanchao Liu, Wenyuan Xue, Yifei Chen, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-survey-hallucination-large-vision-language/)
13. [**World Model on Million-Length Video And Language With Blockwise RingAttention arXiv:2402.08268**Hao Liu, Wilson Yan, Matei Zaharia, et al.*2024 · 99 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-world-model-million-length-video/)
14. **[MANTIS: Interleaved Multi-Image Instruction Tuning](https://md.research.elamur.ai/free/en/papers/jiang-2024-mantis-interleaved-multi-image-instruction/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Dongfu Jiang, Xuan He, Huaye Zeng, et al.*2024 · 74 citations*
15. [**Long Context Transfer from Language to Vision arXiv:2406.16852**Peiyuan Zhang, Kaichen Zhang, Bo Li, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-transfer-language-vision/)
16. [**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/)
17. [**XAttention: Block Sparse Attention with Antidiagonal Scoring arXiv:2503.16428**Ruyi Xu, Guangxuan Xiao, Haofeng Huang, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-xattention-block-sparse-attention-antidiagonal/)
18. **[Stop Looking for “Important Tokens” in Multimodal Language Models: Duplication Matters More](https://md.research.elamur.ai/free/en/papers/wen-2025-stop-looking-important-tokens-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zichen Wen, Yifeng Gao, Shaobo Wang, et al.*2025 · 44 citations*
19. [**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/)
20. **[Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward](https://md.research.elamur.ai/free/en/papers/zhang-2025-direct-preference-optimization-video-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ruohong Zhang, Liangke Gui, Zhiqing Sun, et al.*2025 · 32 citations*
21. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
22. [**Baichuan-Omni Technical Report arXiv:2410.08565**Yadong Li, Haoze Sun, Mingan Lin, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-baichuan-omni-technical-report/)
23. **[What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations](https://md.research.elamur.ai/free/en/papers/liu-2025-what-is-that-talk-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongqi Liu, Chenxi Whitehouse, Xi Yu, et al.*2025 · 13 citations*
24. **[Audio-centric Video Understanding Benchmark without Text Shortcut](https://md.research.elamur.ai/free/en/papers/yang-2025-audio-centric-video-understanding-benchmark/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yudong Yang, Jimin Zhuang, Guangzhi Sun, et al.*2025 · 10 citations*
25. **[SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning](https://md.research.elamur.ai/free/en/papers/ji-2025-specvlm-enhancing-speculative-decoding-video/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yicheng Ji, Jun Zhang, Heming Xia, et al.*2025 · 10 citations*
26. **[TrimTokenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-trimtokenator-adaptive-visual-token-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zhang, Lyu Mengsi, Chenrui He, et al.*2026 · 6 citations*
27. **[VideoPro: Adaptive Program Reasoning for Long Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2026-videopro-adaptive-program-reasoning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenglin Li, Feng Han, Yikun Wang, et al.*2026 · 6 citations*
28. **[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*
29. **[LongVideoAgent: Multi-Agent Reasoning with Long Videos](https://md.research.elamur.ai/free/en/papers/liu-2026-longvideoagent-multi-agent-reasoning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runtao Liu, Ziyi Liu, Jiaqi Tang, et al.*2026 · 3 citations*
30. **[EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence](https://md.research.elamur.ai/free/en/papers/she-2026-echovlm-dynamic-mixture-experts-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoyin She, Ruifang Lu, Lida Chen, et al.*2026 · 1 citation*
31. **[Efficient Table Retrieval and Understanding with Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-efficient-table-retrieval-understanding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyan Xu, Haoyang Fang, Boran Han, et al.*2026 · 1 citation*
32. **[TRACE: Evidence Grounding-Guided Multi-Video Event Understanding and Claim Generation](https://md.research.elamur.ai/free/en/papers/yan-2026-trace-evidence-grounding-guided-multi/) [Workshop on Multimodal Augmented Generation via Multimodal Retrieval](https://md.research.elamur.ai/free/en/venues/magmar/)**Pengyu Yan, Akhil V S S Gorugantu, Mahesh Bhosale, et al.*2026 · 1 citation*
33. **[A Survey of Large Models in Sports](https://md.research.elamur.ai/free/en/papers/xu-2026-survey-large-models-sports/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Xu, Jianzhe Ma, Chuhan Wang, et al.*2026*
34. **[A2O: LLM-based Agentic Learning of Action-to-Object Features for Video Action Recognition](https://md.research.elamur.ai/free/en/papers/sekii-2026-a2o-llm-based-agentic-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taiki Sekii, Fumiaki Sato*2026*
35. **[CAIR: Causal Adaptive Information-based Reinforcement Learning for Multimodal Emotion Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-cair-causal-adaptive-information-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fengyu Zhang, Bin Liu, Jianhua Tao, et al.*2026*
36. **[Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics](https://md.research.elamur.ai/free/en/papers/qiu-2026-can-vlms-predict-future-states/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifu Qiu, Yftah Ziser, Anna Korhonen, et al.*2026*
37. **[Editing the Moving World: Model Editing for Video LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-editing-moving-world-model-editing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Zhang, Xinye Li, Xiaokai Wu, et al.*2026*
38. **[From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration](https://md.research.elamur.ai/free/en/papers/shi-2026-inheritance-saturation-disentangling-evolution-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaqi Shi, Xulong Zhang, Yuechan Li, et al.*2026*
39. **[HowToNarrate: A General-Domain Benchmark for Synchronized Video Narration with External Knowledge](https://md.research.elamur.ai/free/en/papers/wang-2026-howtonarrate-general-domain-benchmark-synchronized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueyan Wang, Dingyi Yang, Qin Jin*2026*
40. **[Learning Flexible Large Multimodal Models with Arbitrary Modality Combinations](https://md.research.elamur.ai/free/en/papers/zhao-2026-learning-flexible-large-multimodal-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhao, Kangqi Ni, Jie Peng, et al.*2026*
41. **[S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language Models](https://md.research.elamur.ai/free/en/papers/shukla-2026-s2h-dpo-hardness-aware-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nitish Shukla, Surgan Jandial, Arun Ross*2026*
42. **[SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter](https://md.research.elamur.ai/free/en/papers/mok-2026-smile-next-teaching-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lee Jung-Mok, Kim Sung-Bin, Joohyun Chang, et al.*2026*
43. **[UNIVID: Unified Vision-Language Model for Video Moderation](https://md.research.elamur.ai/free/en/papers/yang-2026-univid-unified-vision-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kejuan Yang, Yizhuo Zhang, Mingyuan Du, et al.*2026*
44. **[v-HUB: A Benchmark for Video Humor Understanding from Vision and Sound](https://md.research.elamur.ai/free/en/papers/shi-2026-v-hub-benchmark-video-humor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengpeng Shi, Yanpeng Zhao, Jianqun Zhou, et al.*2026*

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