---
title: "Who cites Gemini 1.5: Unlocking multimodal understanding…"
description: "1,221 papers of the Elamur Research library cite «Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context», found in their…"
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---
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# Who cites «Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context»

1,221 papers of our library cite it (of the 140,884 whose bibliographies we read) · 66 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)

1. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)
2. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
3. [**MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/)
4. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 906 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
5. [**MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 731 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/)
6. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
7. [**How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 529 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/)
8. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 524 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
9. [**LLaVA-OneVision: Easy Visual Task Transfer**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 440 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
10. [**Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 403 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/)
11. [**RULER: What's the Real Context Size of Your Long-Context Language Models?**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 386 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
12. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 379 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
13. [**A Survey on Large Language Models for Code Generation**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
14. [**SnapKV: LLM Knows What You are Looking for Before Generation**Yuhong Li, Yingbing Huang, Bowen Yang, et al.*2024 · 350 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-snapkv-llm-knows-looking-before/)
15. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 303 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
16. [**Multimodal Chain-of-Thought Reasoning in Language Models**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2023 · 296 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-multimodal-chain-thought-reasoning-language/)
17. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
18. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
19. [**HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 264 citations*](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/)
20. [**KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache**Zirui Liu, Jiayi Yuan, Hongye Jin, et al.*2024 · 243 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-kivi-tuning-free-asymmetric-2bit/)
21. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
22. [**Qwen2-Audio Technical Report**Yunfei Chu, Jin Xu, Qian Yang, et al.*2024 · 232 citations*](https://md.research.elamur.ai/free/en/papers/chu-2024-qwen2-audio-technical-report/)
23. [**OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments**Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.*2024 · 228 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-osworld-benchmarking-multimodal-agents-open/)
24. [**Qwen2.5-Omni Technical Report**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 218 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
25. [**MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 197 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/)
26. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 195 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
27. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
28. [**What matters when building vision-language models?**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/)
29. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
30. [**Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/)
31. [**Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/)
32. [**Improve Mathematical Reasoning in Language Models by Automated Process Supervision**Liangchen Luo, Yinxiao Liu, Rosanne Liu, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-improve-mathematical-reasoning-language-models/)
33. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
34. [**WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/)
35. [**Moshi: a speech-text foundation model for real-time dialogue**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
36. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 145 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
37. [**Generative Verifiers: Reward Modeling as Next-Token Prediction**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
38. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
39. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 135 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
40. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
41. [**Many-Shot In-Context Learning**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/)
42. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
43. [**Long-context LLMs Struggle with Long In-context Learning**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 132 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/)
44. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 130 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/)
45. [**Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/)
46. [**Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory**Prateek Chhikara, Dev Khant, Saket Aryan, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/chhikara-2025-mem0-building-production-ready-ai/)
47. [**Qwen3-Omni Technical Report**Jin Xu, Zhifang Guo, Hangrui Hu, et al.*2025 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen3-omni-technical-report/)
48. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 104 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/)
49. [**UI-TARS: Pioneering Automated GUI Interaction with Native Agents**Yujia Qin, Yining Ye, Junjie Fang, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/qin-2025-ui-tars-pioneering-automated/)
50. [**Qwen2.5-1M Technical Report**An Yang, Bowen Yu, Chengyuan Li, et al.*2025 · 100 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen2-5-1m-technical/)
51. [**Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Texts**Eleftheria Briakou, Jiaming Luo, Colin Cherry, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2024-translating-step-step-decomposing-translation/)
52. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
53. [**Distillation Scaling Laws**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
54. [**MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks**Mouath Abu Daoud, Chaimae Abouzahir, Leen Kharouf, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/daoud-2025-medarabiq-benchmarking-large-language-models/)
55. [**Comparative Study of Multilingual Idioms and Similes in Large Language Models**Paria Khoshtab, Danial Namazifard, Mostafa Masoudi, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/khoshtab-2025-comparative-study-multilingual-idioms-similes/)
56. [**AIN: The Arabic INclusive Large Multimodal Model**Ahmed Heakl, Sara Ghaboura, Omkar Thawkar, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/heakl-2025-ain-arabic-inclusive-large-multimodal/)
57. [**MultiWikiQA: A Reading Comprehension Benchmark in 300+ Languages**Dan Saattrup Smart*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/smart-2026-multiwikiqa-reading-comprehension-benchmark-300/)
58. [**Arabizi vs LLMs: Can the Genie Understand the Language of Aladdin?**Perla Al Almaoui, Pierrette Bouillon, Simon Hengchen*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/almaoui-2025-arabizi-vs-llms-can-genie/)
59. [**Culturally-Aware Image Captioning for Guaraní with Multimodal Prompting: IUHoosiers at AmericasNLP 2026**Wenchen Shi, Phakphum Artkaew, Luke Gessler*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shi-2026-culturally-aware-image-captioning-guarani/)
60. [**Multi-Agent Interactive Question Generation Framework for Long Document Understanding**Kesen Wang, Daulet Toibazar, Abdulrahman Alfulayt, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/wang-2025-multi-agent-interactive-question-generation/)
61. [**A Large-Scale Instruction-Tuning Dataset and Models for Slovenian Vision-Language Tasks**Matej Martinc, Domen Vreš*2026*](https://md.research.elamur.ai/free/en/papers/martinc-2026-large-scale-instruction-tuning-dataset/)
62. [**HotelCheckSpan: A Benchmark Dataset for LLM Faithfulness**Patricia Schmidtova, Ondrej Dusek, Saad Mahamood*2026*](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-hotelcheckspan-benchmark-dataset-llm-faithfulness/)
63. [**Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation**Zhan Shen, Jason Naradowsky, Xiaotian Wang, et al.*2026*](https://md.research.elamur.ai/free/en/papers/shen-2026-multi-agent-debate-machine-translation/)
64. [**Push and Pull: Training Sentence Encoders with Contrastive Losses for Distance-Based Multi-Label Text Classification**Jens Van Nooten, Andriy Kosar*2026*](https://md.research.elamur.ai/free/en/papers/nooten-2026-push-pull-training-sentence-encoders/)
65. [**Embodied Intelligence Systems Based on Large Models: A Survey (基于大模型的具身智能系统综述)**Wensheng Wang (王文晟), Ning Tan (谭宁), Kai Huang (黄凯), et al.*2025*](https://md.research.elamur.ai/free/en/papers/wang-2025-embodied-intelligence-systems/)
66. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

1,155 more papers of our library cite it; they have no page here yet.

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