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Large language models (LLMs) have achieved remarkable progress in linguistic tasks, necessitating robust evaluation frameworks to understand their capabilities and limitations.
Stochastic resonance and sensory information processing: a tutorial and review of application
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An image is worth 16x16 words: Transformers for image recognition at scale
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Self-instruct: Aligning language models with self-generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Large language models are better reasoners with self-verification
Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Shengping Liu, Bin Sun, Kang Liu, and Jun Zhao · 2022
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
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Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Zhenyu Qiu, Wei Lin, Jinrui Yang, Xiawu Zheng, et al · 2023
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Making llama see and draw with seed tokenizer
Yuying Ge, Sijie Zhao, Ziyun Zeng, Yixiao Ge, Chen Li, Xintao Wang, and Ying Shan · 2023
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Metamath: Bootstrap your own mathematical questions for large language models
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
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Agieval: A human-centric benchmark for evaluating foundation models
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Generating images with multimodal language models
Jing Yu Koh, Daniel Fried, and Ruslan Salakhutdinov · 2023
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Alpacaeval: An automatic evaluator of instruction-following models
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OpenAI · 2023
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Code llama: Open foundation models for code
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Deepseek-coder: When the large language model meets programming–the rise of code intelligence
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Large language model evaluation via matrix entropy
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Leandojo: Theorem proving with retrieval-augmented language models
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