214 resources

  • Rose Wang, Dorottya Demszky
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    Jun 2nd, 2023
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    preprint
    Rose Wang, Dorottya Demszky
    Jun 2nd, 2023

    Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript...

  • EdArXiv
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    Jun 2nd, 2023
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    report
    EdArXiv
    Jun 2nd, 2023

    Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript...

  • Mengxue Zhang, Neil Heffernan, Andrew La...
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    Jun 1st, 2023
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    preprint
    Mengxue Zhang, Neil Heffernan, Andrew La...
    Jun 1st, 2023

    Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score labels. However, since scoring is a subjective process, these human scores are noisy and can be highly variable, depending on the scorer. In this paper,...

  • Mengxue Zhang, Neil Heffernan, Andrew La...
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    Jun 1st, 2023
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    preprint
    Mengxue Zhang, Neil Heffernan, Andrew La...
    Jun 1st, 2023

    Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score labels. However, since scoring is a subjective process, these human scores are noisy and can be highly variable, depending on the scorer. In this paper,...

  • Zach Tilton, John M. LaVelle, Tian Ford,...
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    Jun 1st, 2023
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    journalArticle
    Zach Tilton, John M. LaVelle, Tian Ford,...
    Jun 1st, 2023

    Advancements in Artificial Intelligence (AI) signal a paradigmatic shift with the potential for transforming many various aspects of society, including evaluation education, with implications for subsequent evaluation practice. This article explores the potential implications of AI for evaluator and evaluation education. Specifically, the article discusses key issues in evaluation education including equitable language access to evaluation education, navigating program, social science, and...

  • Zach Tilton, John M. LaVelle, Tian Ford,...
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    Jun 1st, 2023
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    journalArticle
    Zach Tilton, John M. LaVelle, Tian Ford,...
    Jun 1st, 2023

    Advancements in Artificial Intelligence (AI) signal a paradigmatic shift with the potential for transforming many various aspects of society, including evaluation education, with implications for subsequent evaluation practice. This article explores the potential implications of AI for evaluator and evaluation education. Specifically, the article discusses key issues in evaluation education including equitable language access to evaluation education, navigating program, social science, and...

  • May 31st, 2023
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    webpage
    May 31st, 2023

    Following the AI Roadmap suggestions for concrete activities aimed at aligning EU and U.S. risk-based approaches, a group of experts engaged to prepare an initial draft AI terminologies and taxonomies. A total number of 65 terms were identified with reference to key documents from the EU and the U.S.

  • Piotr Sapiezynski, Valentin Kassarnig, C...
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    May 30th, 2023
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    dataset
    Piotr Sapiezynski, Valentin Kassarnig, C...
    May 30th, 2023
  • Yuko Hayashi, Yusuke Kondo, Yutaka Ishii...
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    May 28th, 2023
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    journalArticle
    Yuko Hayashi, Yusuke Kondo, Yutaka Ishii...
    May 28th, 2023
  • Hannibal046
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    May 25th, 2023
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    computerProgram
    Hannibal046
    May 25th, 2023

    Awesome-LLM: a curated list of Large Language Model

  • Susan Lottridge, Chris Ormerod, Amir Jaf...
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    May 25th, 2023
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    bookSection
    Susan Lottridge, Chris Ormerod, Amir Jaf...
    May 25th, 2023
  • Susan Lottridge, Chris Ormerod, Amir Jaf...
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    May 25th, 2023
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    bookSection
    Susan Lottridge, Chris Ormerod, Amir Jaf...
    May 25th, 2023
  • Arjun Kharpal
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    May 24th, 2023
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    webpage
    Arjun Kharpal
    May 24th, 2023

    Artificial intelligence has been thrust into the center of conversations among policymakers grappling with what the tech should look like in the future.

  • Tim Dettmers, Artidoro Pagnoni, Ari Holt...
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    May 23rd, 2023
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    preprint
    Tim Dettmers, Artidoro Pagnoni, Ari Holt...
    May 23rd, 2023

    We present QLoRA, an efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance. QLoRA backpropagates gradients through a frozen, 4-bit quantized pretrained language model into Low Rank Adapters~(LoRA). Our best model family, which we name Guanaco, outperforms all previous openly released models on the Vicuna benchmark, reaching 99.3% of the performance level of ChatGPT while...

  • Reza Hadi Mogavi, Chao Deng, Justin Juho...
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    May 22nd, 2023
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    preprint
    Reza Hadi Mogavi, Chao Deng, Justin Juho...
    May 22nd, 2023

    Understanding user perspectives on Artificial Intelligence (AI) in education is essential for creating pedagogically effective and ethically responsible AI-integrated learning environments. In this paper, we conduct an extensive qualitative content analysis of four major social media platforms (Twitter, Reddit, YouTube, and LinkedIn) to explore the user experience (UX) and perspectives of early adopters toward ChatGPT-an AI Chatbot technology-in various education sectors. We investigate the...

  • Rylan Schaeffer, Brando Miranda, Sanmi K...
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    May 22nd, 2023
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    preprint
    Rylan Schaeffer, Brando Miranda, Sanmi K...
    May 22nd, 2023

    Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability, appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family,...

  • May 21st, 2023
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    magazineArticle
    May 21st, 2023
  • Noah Shinn, Federico Cassano, Beck Labas...
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    May 21st, 2023
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    preprint
    Noah Shinn, Federico Cassano, Beck Labas...
    May 21st, 2023

    Large language models (LLMs) have been increasingly used to interact with external environments (e.g., games, compilers, APIs) as goal-driven agents. However, it remains challenging for these language agents to quickly and efficiently learn from trial-and-error as traditional reinforcement learning methods require extensive training samples and expensive model fine-tuning. We propose Reflexion, a novel framework to reinforce language agents not by updating weights, but instead through...

  • May 19th, 2023
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    webpage
    May 19th, 2023

    Stanford experts examine the safety and accuracy of GPT-4 in serving curbside consultation needs of doctors.

  • Rohan Anil, Andrew M. Dai, Orhan Firat
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    May 17th, 2023
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    preprint
    Rohan Anil, Andrew M. Dai, Orhan Firat
    May 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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