11 resources

  • Wenchao Li, Haitao Liu
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    Jun 3rd, 2024
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    journalArticle
    Wenchao Li, Haitao Liu
    Jun 3rd, 2024

    Recent advancements in artificial intelligence (AI) have led to an increased use of large language models (LLMs) for language assessment tasks such as automated essay scoring (AES), automated listening tests, and automated oral proficiency assessments. The application of LLMs for AES in the context of non-native Japanese, however, remains limited. This study explores the potential of LLM-based AES by comparing the efficiency of different models, i.e. two conventional machine training...

  • Liu
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    Aug 22nd, 2024
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    conferencePaper
    Liu
    Aug 22nd, 2024
  • Zheng Chu, Jingchang Chen, Qianglong Che...
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    Jan 22nd, 2024
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    preprint
    Zheng Chu, Jingchang Chen, Qianglong Che...
    Jan 22nd, 2024

    Reasoning, a fundamental cognitive process integral to human intelligence, has garnered substantial interest within artificial intelligence. Notably, recent studies have revealed that chain-of-thought prompting significantly enhances LLM's reasoning capabilities, which attracts widespread attention from both academics and industry. In this paper, we systematically investigate relevant research, summarizing advanced methods through a meticulous taxonomy that offers novel perspectives....

  • Gyeong-Geon Lee, Ehsan Latif, Xuansheng ...
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    Jun 22nd, 2024
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    preprint
    Gyeong-Geon Lee, Ehsan Latif, Xuansheng ...
    Jun 22nd, 2024

    This study investigates the application of large language models (LLMs), specifically GPT-3.5 and GPT-4, with Chain-of-Though (CoT) in the automatic scoring of student-written responses to science assessments. We focused on overcoming the challenges of accessibility, technical complexity, and lack of explainability that have previously limited the use of artificial intelligence-based automatic scoring tools among researchers and educators. With a testing dataset comprising six assessment...

  • Gyeong-Geon Lee, Ehsan Latif, Xuansheng ...
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    Jun 22nd, 2024
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    journalArticle
    Gyeong-Geon Lee, Ehsan Latif, Xuansheng ...
    Jun 22nd, 2024
  • Yiqing Xie, Alex Xie, Divyanshu Sheth
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    Mar 31st, 2024
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    preprint
    Yiqing Xie, Alex Xie, Divyanshu Sheth
    Mar 31st, 2024

    To facilitate evaluation of code generation systems across diverse scenarios, we present CodeBenchGen, a framework to create scalable execution-based benchmarks that only requires light guidance from humans. Specifically, we leverage a large language model (LLM) to convert an arbitrary piece of code into an evaluation example, including test cases for execution-based evaluation. We illustrate the usefulness of our framework by creating a dataset, Exec-CSN, which includes 1,931 examples...

  • Steven Moore, Eamon Costello, Huy A. Ngu...
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    Jan 22nd, 2024
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    bookSection
    Steven Moore, Eamon Costello, Huy A. Ngu...
    Jan 22nd, 2024
  • Okan Bulut, Maggie Beiting-Parrish, Jodi...
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    Jun 27th, 2024
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    preprint
    Okan 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...

  • Okan Bulut, Maggie Beiting-Parrish, Jodi...
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    Jan 22nd, 2024
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    preprint
    Okan 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...

  • Hua Shen, Tiffany Knearem, Reshmi Ghosh,...
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    Aug 10th, 2024
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    preprint
    Hua 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...

  • Abhimanyu Dubey, Abhinav Jauhri, Abhinav...
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    Aug 15th, 2024
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    preprint
    Abhimanyu 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...

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