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59 resources
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Gautam Yadav, Ying-Jui Tseng, Xiaolin Ni...|Jul 7th, 2023|conferencePaperGautam Yadav, Ying-Jui Tseng, Xiaolin Ni...Jul 7th, 2023
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Qianou Christina Ma, Sherry Tongshuang W...|Jul 7th, 2023|conferencePaperQianou Christina Ma, Sherry Tongshuang W...Jul 7th, 2023
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Benjamin D. Nye, Dillon Mee, Mark G. Cor...|Jul 7th, 2023|conferencePaperBenjamin D. Nye, Dillon Mee, Mark G. Cor...Jul 7th, 2023
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Shouvik Ahmed Antu, Haiyan Chen, Cindy K...|Jul 7th, 2023|conferencePaperShouvik Ahmed Antu, Haiyan Chen, Cindy K...Jul 7th, 2023
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Bor-Chen Kuo, Frederic T. Y. Chang, Zong...|Jul 7th, 2023|conferencePaperBor-Chen Kuo, Frederic T. Y. Chang, Zong...Jul 7th, 2023
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Daniel Leiker, Sara Finnigan, Ashley Ric...|Jul 7th, 2023|conferencePaperDaniel Leiker, Sara Finnigan, Ashley Ric...Jul 7th, 2023
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Alex Goslen, Yeo Jin Kim, Jonathan Rowe,...|Jul 7th, 2023|conferencePaperAlex Goslen, Yeo Jin Kim, Jonathan Rowe,...Jul 7th, 2023
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Pragnya Sridhar, Aidan Doyle, Arav Agarw...|Jul 7th, 2023|conferencePaperPragnya Sridhar, Aidan Doyle, Arav Agarw...Jul 7th, 2023
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Muntasir Hoq, Yang Shi, Juho Leinonen|Jul 7th, 2023|conferencePaperMuntasir Hoq, Yang Shi, Juho LeinonenJul 7th, 2023
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Sai Gattupalli, Will Lee, Danielle Alles...|Jul 7th, 2023|conferencePaperSai Gattupalli, Will Lee, Danielle Alles...Jul 7th, 2023
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Iddo Drori, Sarah Zhang, Reece Shuttlewo...|Aug 2nd, 2022|journalArticleIddo Drori, Sarah Zhang, Reece Shuttlewo...Aug 2nd, 2022
We demonstrate that a neural network pretrained on text and fine-tuned on code solves mathematics course problems, explains solutions, and generates questions at a human level. We automatically synthesize programs using few-shot learning and OpenAI’s Codex transformer and execute them to solve course problems at 81% automatic accuracy. We curate a dataset of questions from Massachusetts Institute of Technology (MIT)’s largest mathematics courses (Single Variable and Multivariable Calculus,...
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Katie Bainbridge, Candace Walkington, Ar...|Jul 7th, 2023|conferencePaperKatie Bainbridge, Candace Walkington, Ar...Jul 7th, 2023
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Kole Norberg, Husni Almoubayyed, Stephen...|Jul 7th, 2023|conferencePaperKole Norberg, Husni Almoubayyed, Stephen...Jul 7th, 2023
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The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical ChallengesOkan Bulut, Maggie Beiting-Parrish, Jodi...|Jun 27th, 2024|preprintOkan Bulut, Maggie Beiting-Parrish, Jodi...Jun 27th, 2024
The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid content analysis, and personalized feedback through machine learning and natural language processing. These advancements provide timely, consistent feedback and valuable insights into student performance, thereby enhancing the assessment experience. However, the deployment of AI in education also raises significant ethical concerns regarding...
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The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical ChallengesOkan Bulut, Maggie Beiting-Parrish, Jodi...|Jan 22nd, 2024|preprintOkan Bulut, Maggie Beiting-Parrish, Jodi...Jan 22nd, 2024
The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid content analysis, and personalized feedback through machine learning and natural language processing. These advancements provide timely, consistent feedback and valuable insights into student performance, thereby enhancing the assessment experience. However, the deployment of AI in education also raises significant ethical concerns regarding...
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Hua Shen, Tiffany Knearem, Reshmi Ghosh,...|Aug 10th, 2024|preprintHua Shen, Tiffany Knearem, Reshmi Ghosh,...Aug 10th, 2024
Recent advancements in general-purpose AI have highlighted the importance of guiding AI systems towards the intended goals, ethical principles, and values of individuals and groups, a concept broadly recognized as alignment. However, the lack of clarified definitions and scopes of human-AI alignment poses a significant obstacle, hampering collaborative efforts across research domains to achieve this alignment. In particular, ML- and philosophy-oriented alignment research often views AI...
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Andrew Caines, Luca Benedetto, Shiva Tas...|Jul 7th, 2023|conferencePaperAndrew Caines, Luca Benedetto, Shiva Tas...Jul 7th, 2023
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Rohan Anil, Andrew M. Dai, Orhan Firat|May 17th, 2023|preprintRohan Anil, Andrew M. Dai, Orhan FiratMay 17th, 2023
We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives. Through extensive evaluations on English and multilingual language, and reasoning tasks, we demonstrate that PaLM 2 has significantly improved quality on downstream tasks across different model sizes, while simultaneously exhibiting faster and more...
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav...|Aug 15th, 2024|preprintAbhimanyu Dubey, Abhinav Jauhri, Abhinav...Aug 15th, 2024
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language...