---
title: "Who cites Kefan Xiao — 4,375 papers of our library"
description: "4,375 papers of the Elamur Research library cite the works of Kefan Xiao, found in their bibliographies · page 1 of 11 · 1–100; the most cited first."
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---
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# Who cites Kefan Xiao

4,818 citations of their works from 4,375 papers of our library (of the 149,439 whose bibliographies we read) · 1,061 with a page here, the most cited first · page 1 of 11 · 1–100 · [← Kefan Xiao](https://md.research.elamur.ai/free/en/authors/kefan-xiao/)

**1** [2](https://md.research.elamur.ai/free/en/authors/kefan-xiao/cited-by/page/2/) … [10](https://md.research.elamur.ai/free/en/authors/kefan-xiao/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/authors/kefan-xiao/cited-by/page/11/) [next →](https://md.research.elamur.ai/free/en/authors/kefan-xiao/cited-by/page/2/)

1. [**Llama 2: Open Foundation and Fine-Tuned Chat Models arXiv:2307.09288**Hugo Touvron, Louis Martin, Kevin Stone, et al.*2023 · 9,669 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2023-llama-2-open-foundation-fine/)
2. [**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/)
3. **[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*
4. **[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*
5. [**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/)
6. **[QLoRA: Efficient Finetuning of Quantized LLMs](https://md.research.elamur.ai/free/en/papers/dettmers-2023-qlora-efficient-finetuning-quantized-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.*2023 · 2,929 citations*
7. **[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*
8. [**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/)
9. [**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/)
10. [**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/)
11. [**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/)
12. **[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*
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. [**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/)
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. **[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*
17. [**PaLM 2 Technical Report arXiv:2305.10403**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 1,000 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/)
18. [**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/)
19. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond arXiv:2308.12966**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 970 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
20. **[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*
21. [**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/)
22. **[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*
23. **[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*
24. [**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/)
25. [**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/)
26. **[Video-LLaVA: Learning United Visual Representation by Alignment Before Projection](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 627 citations*
27. [**Instruction-Following Evaluation for Large Language Models arXiv:2311.07911**Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.*2023 · 615 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-instruction-following-evaluation-large-language/)
28. [**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/)
29. [**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/)
30. [**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/)
31. [**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/)
32. **[SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Carlos E. Jimenez, Alexander Wettig, et al.*2024 · 552 citations*
33. [**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/)
34. **[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*
35. [**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/)
36. [**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/)
37. **[Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations](https://md.research.elamur.ai/free/en/papers/wang-2024-math-shepherd-verify-reinforce-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiyi Wang, Lei Li, Zhihong Shao, et al.*2024 · 497 citations*
38. [**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/)
39. [**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/)
40. **[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*
41. [**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/)
42. [**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/)
43. [**Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models arXiv:2401.01301 · Journal of Legal Analysis 16, no. 1 (2024): 64-93**Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.*2024 · 437 citations*](https://md.research.elamur.ai/free/en/papers/dahl-2024-large-legal-fictions-profiling-legal/)
44. [**AgentBench: Evaluating LLMs as Agents arXiv:2308.03688**Xiao Liu, Hao Yu, Hanchen Zhang, et al.*2023 · 432 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-agentbench-evaluating-llms-agents/)
45. [**WebArena: A Realistic Web Environment for Building Autonomous Agents arXiv:2307.13854**Shuyan Zhou, Frank F. Xu, Hao Zhu, et al.*2023 · 432 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-webarena-realistic-web-environment-building/)
46. [**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/)
47. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 430 citations*
48. **[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*
49. [**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/)
50. [**Large Language Models as Optimizers arXiv:2309.03409**Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.*2023 · 413 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/)
51. [**Large Language Models Cannot Self-Correct Reasoning Yet arXiv:2310.01798**Jie Huang, Xinyun Chen, Swaroop Mishra, et al.*2023 · 412 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-cannot-self/)
52. **[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*
53. [**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/)
54. [**FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU arXiv:2303.06865**Ying Sheng, Lianmin Zheng, Binhang Yuan, et al.*2023 · 402 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2023-flexgen-high-throughput-generative-inference/)
55. [**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/)
56. [**Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations arXiv:2312.06674**Hakan Inan, Kartikeya Upasani, Jianfeng Chi, et al.*2023 · 395 citations*](https://md.research.elamur.ai/free/en/papers/inan-2023-llama-guard-llm-based-input/)
57. **[Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity](https://md.research.elamur.ai/free/en/papers/jeong-2024-adaptive-rag-learning-adapt-retrieval/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.*2024 · 382 citations*
58. **[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*
59. [**Splitwise: Efficient generative LLM inference using phase splitting ISCA 2024**Pratyush Patel, Esha Choukse, Chaojie Zhang, et al.*2023 · 379 citations*](https://md.research.elamur.ai/free/en/papers/patel-2023-splitwise-efficient-generative-llm-inference/)
60. [**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/)
61. [**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/)
62. [**Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve OSDI 2024**Amey Agrawal, Nitin Kedia, Ashish Panwar, et al.*2024 · 369 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-taming-throughput-latency-tradeoff-llm/)
63. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
64. **[BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 362 citations*
65. **[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*
66. [**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/)
67. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
68. **[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*
69. [**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/)
70. [**"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models arXiv:2308.03825**Xinyue Shen, Zeyuan Chen, Michael Backes, et al.*2023 · 329 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-anything-now-characterizing-evaluating-wild/)
71. [**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/)
72. **[Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-eyes-wide-shut-exploring-visual/) [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/)**Shengbang Tong, Zhuang Liu, Yuexiang Zhai, et al.*2024 · 321 citations*
73. **[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*
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