62 resources

  • Rose E. Wang, Qingyang Zhang, Carly Robi...
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    Apr 28th, 2024
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    preprint
    Rose E. Wang, Qingyang Zhang, Carly Robi...
    Apr 28th, 2024

    Scaling high-quality tutoring remains a major challenge in education. Due to growing demand, many platforms employ novice tutors who, unlike experienced educators, struggle to address student mistakes and thus fail to seize prime learning opportunities. Our work explores the potential of large language models (LLMs) to close the novice-expert knowledge gap in remediating math mistakes. We contribute Bridge, a method that uses cognitive task analysis to translate an expert's latent thought...

  • Ziwei Xu, Sanjay Jain, Mohan Kankanhalli...
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    Apr 28th, 2024
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    journalArticle
    Ziwei Xu, Sanjay Jain, Mohan Kankanhalli...
    Apr 28th, 2024

    Hallucination has been widely recognized to be a significant drawback for large language models (LLMs). There have been many works that attempt to reduce the extent of hallucination. These efforts have mostly been empirical so far, which cannot answer the fundamental question whether it can be completely eliminated. In this paper, we formalize the problem and show that it is impossible to eliminate hallucination in LLMs. Specifically, we define a formal world where hallucination is defined...

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