---
title: "Who cites Gemini Robotics Team — 3,373 papers of our library"
description: "3,373 papers of the Elamur Research library cite the works of Gemini Robotics Team, found in their bibliographies · page 1 of 7 · 1–100; the…"
canonical: "https://research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Gemini Robotics Team](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/) / cited by

# Who cites Gemini Robotics Team

3,574 citations of their works from 3,373 papers of our library (of the 149,439 whose bibliographies we read) · 684 with a page here, the most cited first · page 1 of 7 · 1–100 · [← Gemini Robotics Team](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/)

**1** [2](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/page/2/) … [7](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/page/7/) [next →](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/page/2/)

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. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,115 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
4. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arXiv:2403.05530**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
5. **[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*
6. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone arXiv:2404.14219**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,134 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
7. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
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. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 974 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
10. **[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*
11. [**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/)
12. **[MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 761 citations*
13. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 729 citations*
14. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools arXiv:2406.12793**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 691 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
15. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
16. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters arXiv:2408.03314**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 567 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
17. [**Jailbreaking Black Box Large Language Models in Twenty Queries arXiv:2310.08419**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 553 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
18. [**Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference arXiv:2403.04132**Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.*2024 · 546 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2024-chatbot-arena-open-platform-evaluating/)
19. **[How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 541 citations*
20. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
21. [**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/)
22. [**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/)
23. **[OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems](https://md.research.elamur.ai/free/en/papers/he-2024-olympiadbench-challenging-benchmark-promoting-agi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.*2024 · 456 citations*
24. [**FinGPT: Open-Source Financial Large Language Models arXiv:2306.06031**Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang*2023 · 445 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-fingpt-open-source-financial-large/)
25. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs arXiv:2501.12599**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
26. **[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*
27. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
28. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 409 citations*
29. [**Yi: Open Foundation Models by 01.AI arXiv:2403.04652**Alex Young, Bei Chen, Chao Li, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
30. [**RULER: What's the Real Context Size of Your Long-Context Language Models? arXiv:2404.06654**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 400 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
31. **[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*
32. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery arXiv:2408.06292**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 372 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
33. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct arXiv:2308.09583**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 372 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
34. [**Qwen3-VL Technical Report arXiv:2511.21631**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 370 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/)
35. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
36. **[SnapKV: LLM Knows What You are Looking for Before Generation](https://md.research.elamur.ai/free/en/papers/li-2024-snapkv-llm-knows-looking-before/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuhong Li, Yingbing Huang, Bowen Yang, et al.*2024 · 355 citations*
37. **[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*
38. [**HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal arXiv:2402.04249**Mantas Mazeika, Long Phan, Xuwang Yin, et al.*2024 · 330 citations*](https://md.research.elamur.ai/free/en/papers/mazeika-2024-harmbench-standardized-evaluation-framework-automated/)
39. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
40. **[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*
41. [**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/)
42. **[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*
43. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
44. **[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*
45. **[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*
46. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models arXiv:2410.05229**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
47. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
48. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies arXiv:2404.06395**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
49. **[HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 268 citations*
50. **[OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments](https://md.research.elamur.ai/free/en/papers/xie-2024-osworld-benchmarking-multimodal-agents-open/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.*2024 · 264 citations*
51. **[The Effect of Sampling Temperature on Problem Solving in Large Language Models](https://md.research.elamur.ai/free/en/papers/renze-2024-effect-sampling-temperature-problem-solving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Renze*2024 · 263 citations*
52. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
53. **[Humanity's Last Exam](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/) [Nature](https://md.research.elamur.ai/free/en/venues/nature/)**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 256 citations*
54. **[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*
55. [**KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache arXiv:2402.02750**Zirui Liu, Jiayi Yuan, Hongye Jin, et al.*2024 · 244 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/)
56. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
57. [**Qwen2-Audio Technical Report arXiv:2407.10759**Yunfei Chu, Jin Xu, Qian Yang, et al.*2024 · 238 citations*](https://md.research.elamur.ai/free/en/papers/chu-2024-qwen2-audio-technical-report/)
58. **[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*
59. [**Qwen2.5-Omni Technical Report arXiv:2503.20215**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 227 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
60. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models arXiv:2405.17428**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 222 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
61. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 221 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
62. **[Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models](https://md.research.elamur.ai/free/en/papers/levy-2024-same-task-more-tokens-impact/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mosh Levy, Alon Jacoby, Yoav Goldberg*2024 · 217 citations*
63. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
64. **[Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/) [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/)**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 216 citations*
65. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 212 citations*
66. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline arXiv:2406.11939**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 210 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
67. [**DeepSeek-VL: Towards Real-World Vision-Language Understanding arXiv:2403.05525**Haoyu Lu, Wen Liu, Bo Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-deepseek-vl-real-world/)
68. **[Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset](https://md.research.elamur.ai/free/en/papers/wang-2024-measuring-multimodal-mathematical-reasoning-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ke Wang, Junting Pan, Weikang Shi, et al.*2024 · 203 citations*
69. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 202 citations*
70. **[ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search](https://md.research.elamur.ai/free/en/papers/zhang-2024-rest-mcts-llm-self-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.*2024 · 200 citations*
71. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence arXiv:2406.11931**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
72. **[LLM in a flash: Efficient Large Language Model Inference with Limited Memory](https://md.research.elamur.ai/free/en/papers/alizadeh-2024-llm-flash-efficient-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.*2024 · 193 citations*
73. **[WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/he-2024-webvoyager-building-end-end-web/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2024 · 191 citations*
74. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
75. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier arXiv:2412.04261**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
76. **[Towards Building Multilingual Language Model for Medicine](https://md.research.elamur.ai/free/en/papers/qiu-2024-towards-building-multilingual-language-model/) [Nature Communications](https://md.research.elamur.ai/free/en/venues/nature-communications/)**Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang, et al.*2024 · 184 citations*
77. **[VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 184 citations*
78. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
79. **[Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 179 citations*
80. **[Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 178 citations*
81. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
82. [**Aya 23: Open Weight Releases to Further Multilingual Progress arXiv:2405.15032**Viraat Aryabumi, John Dang, Dwarak Talupuru, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/aryabumi-2024-aya-23-open-weight-releases/)
83. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
84. [**Improve Mathematical Reasoning in Language Models by Automated Process Supervision arXiv:2406.06592**Liangchen Luo, Yinxiao Liu, Rosanne Liu, et al.*2024 · 168 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-improve-mathematical-reasoning-language-models/)
85. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models arXiv:2508.06471**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 166 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/)
86. **[MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 166 citations*
87. **[Long-form factuality in large language models](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 165 citations*
88. **[WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 165 citations*
89. [**Chameleon: Mixed-Modal Early-Fusion Foundation Models arXiv:2405.09818**Chameleon Team*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-chameleon-mixed-modal-early-fusion/)
90. [**Moshi: a speech-text foundation model for real-time dialogue arXiv:2410.00037**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 157 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
91. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
92. **[BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages](https://md.research.elamur.ai/free/en/papers/myung-2024-blend-benchmark-llms-everyday-knowledge/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Junho Myung, Nayeon Lee, Yi Zhou, et al.*2024 · 152 citations*
93. [**Generative Verifiers: Reward Modeling as Next-Token Prediction arXiv:2408.15240**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 152 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
94. [**GPT-4V(ision) is a Generalist Web Agent, if Grounded arXiv:2401.01614**Boyuan Zheng, Boyu Gou, Jihyung Kil, et al.*2024 · 146 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-gpt-4v-ision-generalist-web/)
95. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 142 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
96. **[Many-Shot In-Context Learning](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 142 citations*
97. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 141 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
98. [**Long-context LLMs Struggle with Long In-context Learning arXiv:2404.02060**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
99. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
100. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)

**1** [2](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/page/2/) … [7](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/page/7/) [next →](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/cited-by/page/2/)

- [← back to](https://md.research.elamur.ai/free/en/authors/gemini-robotics-team/) — Gemini Robotics Team