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We present a new challenge to examine whether large language models understand social norms.
Language models are few-shot learners
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Long short-term memory
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Language models are open knowledge graphs
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Understanding the ixl smartscore
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On calibration of modern neural networks
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The impact of ixl math and ixl ela on student achievement in grades pre-k to 12
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Compressing recurrent neural networks with tensor ring for action recognition
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
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Ixl design principles
Bozhidar M Bashkov, Kate Mattison, and Lara Hochstein. 2021 · 2021
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Holistic evaluation of language models
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Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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Palt: parameter-lite transfer of language models for knowledge graph completion
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
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DeepStruct: Pretraining of language models for structure prediction
Camel: Communicative agents for" mind" exploration of large scale language model society
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Taskmatrix.ai: Completing tasks by connecting foundation models with millions of apis
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Toolformer: Language models can teach themselves to use tools
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Large language models can be easily distracted by irrelevant context
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Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, and Dawn Song. 2022 · 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 · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
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How is chatgpt’s behavior changing over time?
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Palm: Scaling language modeling with pathways
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Agent instructs large language models to be general zero-shot reasoners
Nicholas Crispino, Kyle Montgomery, Fankun Zeng, Dawn Song, and Chenguang Wang. 2023 · 2023
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Gemini: A family of highly capable multimodal models
Google Gemini Team. 2023 · 2023
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Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H Chi, Nathanael Schärli, and Denny Zhou. 2023 · 2023
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Alpaca: A strong, replicable instruction-following model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Creating large language model applications utilizing langchain: A primer on developing llm apps fast
Oguzhan Topsakal and Tahir Cetin Akinci. 2023 · 2023
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Chatlog: Recording and analyzing chatgpt across time
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The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al. 2023 · 2023
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Exchange-of-thought: Enhancing large language model capabilities through cross-model communication
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Preparing lessons for progressive training on language models
Yu Pan, Ye Yuan, Yichun Yin, Jiaxin Shi, Zenglin Xu, Ming Zhang, Lifeng Shang, Xin Jiang, and Qun Liu. 2024 · 2024
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Measuring vision-language stem skills of neural models
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