---
title: "Who cites Tri Dao — 3,531 papers of our library"
description: "3,531 papers of the Elamur Research library cite the works of Tri Dao, found in their bibliographies · page 1 of 5 · 1–100; the most cited first."
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# Who cites Tri Dao

5,065 citations of their works from 3,531 papers of our library (of the 149,439 whose bibliographies we read) · 462 with a page here, the most cited first · page 1 of 5 · 1–100 · [← Tri Dao](https://md.research.elamur.ai/free/en/authors/tri-dao/)

**1** [2](https://md.research.elamur.ai/free/en/authors/tri-dao/cited-by/page/2/) … [5](https://md.research.elamur.ai/free/en/authors/tri-dao/cited-by/page/5/) [next →](https://md.research.elamur.ai/free/en/authors/tri-dao/cited-by/page/2/)

1. [**LLaMA: Open and Efficient Foundation Language Models arXiv:2302.13971**Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.*2023 · 9,603 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2023-llama-open-efficient-foundation-language/)
2. **[Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://md.research.elamur.ai/free/en/papers/zheng-2023-judging-llm-judge-mt-bench/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.*2023 · 4,573 citations*
3. **[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*
4. **[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*
5. **[Lost in the Middle: How Language Models Use Long Contexts](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,584 citations*
6. **[Reflexion: Language Agents with Verbal Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shinn-2023-reflexion-language-agents-verbal-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Noah Shinn, Federico Cassano, Edward Berman, et al.*2023 · 2,271 citations*
7. [**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/)
8. [**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/)
9. [**DINOv2: Learning Robust Visual Features without Supervision arXiv:2304.07193**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
10. [**Code Llama: Open Foundation Models for Code arXiv:2308.12950**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,430 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/)
11. **[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*
12. [**FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning arXiv:2307.08691**Tri Dao*2023 · 1,240 citations*](https://md.research.elamur.ai/free/en/papers/dao-2023-flashattention-2-faster-attention-better/)
13. [**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/)
14. **[LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,048 citations*
15. **[GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ainslie, James Lee-Thorp, Michiel de Jong, et al.*2023 · 1,026 citations*
16. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/)
17. **[C-Pack: Packed Resources For General Chinese Embeddings](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 922 citations*
18. [**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/)
19. **[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*
20. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues? arXiv:2310.06770**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 704 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
21. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
22. [**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/)
23. [**Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection arXiv:2310.11511**Akari Asai, Zeqiu Wu, Yizhong Wang, et al.*2023 · 677 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-self-rag-learning-retrieve-generate/)
24. [**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/)
25. [**gpt-oss-120b & gpt-oss-20b Model Card arXiv:2508.10925**OpenAI: Sandhini Agarwal, Lama Ahmad, Jason Ai, et al.*2025 · 576 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-gpt-oss-120b-gpt-oss/)
26. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models arXiv:2309.12284**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 565 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
27. [**Qwen2.5-Coder Technical Report arXiv:2409.12186**Binyuan Hui, Jian Yang, Zeyu Cui, et al.*2024 · 559 citations*](https://md.research.elamur.ai/free/en/papers/hui-2024-qwen2-5-coder-technical-report/)
28. **[Gorilla: Large Language Model Connected with Massive APIs](https://md.research.elamur.ai/free/en/papers/patil-2023-gorilla-large-language-model-connected/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.*2023 · 546 citations*
29. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 520 citations*
30. [**Baichuan 2: Open Large-scale Language Models arXiv:2309.10305**Aiyuan Yang, Bin Xiao, Bingning Wang, et al.*2023 · 517 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-baichuan-2-open-large-scale/)
31. **[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*
32. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
33. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks arXiv:2312.14238**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 435 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
34. [**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/)
35. **[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*
36. [**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/)
37. **[FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision](https://md.research.elamur.ai/free/en/papers/shah-2024-flashattention-3-fast-accurate-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jay Shah, Ganesh Bikshandi, Ying Zhang, et al.*2024 · 400 citations*
38. [**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/)
39. [**LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models arXiv:2308.11462**Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li*2023 · 389 citations*](https://md.research.elamur.ai/free/en/papers/guha-2023-legalbench-collaboratively-built-benchmark-measuring/)
40. [**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/)
41. [**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/)
42. [**Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference arXiv:2412.13663**Benjamin Warner, Antoine Chaffin, Benjamin Clavié, et al.*2024 · 358 citations*](https://md.research.elamur.ai/free/en/papers/warner-2024-smarter-better-faster-longer-modern/)
43. **[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*
44. [**TinyLlama: An Open-Source Small Language Model arXiv:2401.02385**Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.*2024 · 352 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-tinyllama-open-source-small-language/)
45. [**Textbooks Are All You Need II: phi-1.5 technical report arXiv:2309.05463**Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, et al.*2023 · 336 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-textbooks-all-need-ii-phi/)
46. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
47. [**InternLM2 Technical Report arXiv:2403.17297**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
48. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
49. [**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/)
50. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
51. **[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*
52. [**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/)
53. [**LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models arXiv:2309.12307**Yukang Chen, Shengju Qian, Haotian Tang, et al.*2023 · 268 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-longlora-efficient-fine-tuning-long/)
54. [**Retentive Network: A Successor to Transformer for Large Language Models arXiv:2307.08621**Yutao Sun, Li Dong, Shaohan Huang, et al.*2023 · 265 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-retentive-network-successor-transformer-large/)
55. **[RedPajama: an Open Dataset for Training Large Language Models](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 260 citations*
56. **[Fine-Tuning LLaMA for Multi-Stage Text Retrieval](https://md.research.elamur.ai/free/en/papers/ma-2023-fine-tuning-llama-multi-stage/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Xueguang Ma, Liang Wang, Nan Yang, et al.*2023 · 257 citations*
57. **[QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 254 citations*
58. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
59. **[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*
60. **[LeanDojo: Theorem Proving with Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/yang-2023-leandojo-theorem-proving-retrieval-augmented/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.*2023 · 253 citations*
61. [**Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture arXiv:2306.16092**Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-chatlaw-multi-agent-legal-assistant/)
62. [**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/)
63. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 237 citations*
64. [**ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving arXiv:2309.17452**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 225 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-tora-tool-integrated-reasoning-agent/)
65. [**Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment arXiv:2308.05374**Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-trustworthy-llms-survey-guideline-evaluating/)
66. [**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/)
67. **[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*
68. [**Ring Attention with Blockwise Transformers for Near-Infinite Context arXiv:2310.01889**Hao Liu, Matei Zaharia, Pieter Abbeel*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ring-attention-blockwise-transformers-near/)
69. [**LIMO: Less is More for Reasoning arXiv:2502.03387**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 209 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/)
70. [**EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty arXiv:2401.15077**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/)
71. [**Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference arXiv:2406.10774**Jiaming Tang, Yilong Zhao, Kan Zhu, et al.*2024 · 203 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-quest-query-aware-sparsity-efficient/)
72. [**AlphaEvolve: A coding agent for scientific and algorithmic discovery arXiv:2506.13131**Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.*2025 · 202 citations*](https://md.research.elamur.ai/free/en/papers/novikov-2025-alphaevolve-coding-agent-scientific-algorithmic/)
73. **[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*
74. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs arXiv:2310.01801**Suyu Ge, Yunan Zhang, Liyuan Liu, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/)
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76. [**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/)
77. [**OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models arXiv:2308.13137**Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, et al.*2023 · 195 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-omniquant-omnidirectionally-calibrated-quantization-large/)
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81. [**CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer arXiv:2408.06072**Zhuoyi Yang, Jiayan Teng, Wendi Zheng, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-cogvideox-text-video-diffusion/)
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84. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model arXiv:2502.02737**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 181 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
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86. [**KernelBench: Can LLMs Write Efficient GPU Kernels? arXiv:2502.10517**Anne Ouyang, Simon Guo, Simran Arora, et al.*2025 · 178 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2025-kernelbench-llms-write-efficient-gpu/)
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88. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
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91. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas arXiv:2406.20094**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/)
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93. [**ShortGPT: Layers in Large Language Models are More Redundant Than You Expect arXiv:2403.03853**Xin Men, Mingyu Xu, Qingyu Zhang, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/men-2024-shortgpt-layers-large-language-models/)
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97. [**From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning arXiv:2308.12032**Ming Li, Yong Zhang, Zhitao Li, et al.*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-quantity-quality-boosting-llm-performance/)
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