4 resources

  • Rose E. Wang, Qingyang Zhang, Carly Robi...
    |
    Apr 4th, 2024
    |
    preprint
    Rose E. Wang, Qingyang Zhang, Carly Robi...
    Apr 4th, 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...

  • Joshua Wilson, Fan Zhang, Corey Palermo,...
    |
    Apr 1st, 2024
    |
    journalArticle
    Joshua Wilson, Fan Zhang, Corey Palermo,...
    Apr 1st, 2024

    This study examined middle school students' perceptions of an automated writing evaluation (AWE) system, MI Write. We summarize students' perceptions of MI Write's usability, usefulness, and desirability both quantitatively and qualitatively. We then estimate hierarchical entry regression models that account for district context, classroom climate, demographic factors (i.e., gender, special education status, limited English proficiency status, socioeconomic status, grade), students'...

  • Hugh Zhang, Jeff Da, Dean Lee
    |
    May 3rd, 2024
    |
    preprint
    Hugh Zhang, Jeff Da, Dean Lee
    May 3rd, 2024

    Large language models (LLMs) have achieved impressive success on many benchmarks for mathematical reasoning. However, there is growing concern that some of this performance actually reflects dataset contamination, where data closely resembling benchmark questions leaks into the training data, instead of true reasoning ability. To investigate this claim rigorously, we commission Grade School Math 1000 (GSM1k). GSM1k is designed to mirror the style and complexity of the established GSM8k...

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

Last update from database: 04/04/2025, 02:15 (UTC)
Powered by Zotero and Kerko.