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New dataset Exposía benchmarks LLMs for academic writing assessment

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced Exposía, a novel dataset designed to advance computational approaches in academic writing education. This dataset comprises student research proposals, peer feedback, and instructor assessments, facilitating research into teaching and evaluating writing skills. Benchmarking large language models on Exposía revealed that closed-source models generally outperform open-weight models, and a multi-aspect scoring strategy proved most effective for classroom applications. AI

IMPACT This dataset could enable more effective AI-powered tools for academic writing assistance and assessment in educational settings.

RANK_REASON The cluster describes a new academic paper introducing a dataset and benchmarking LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset Exposía benchmarks LLMs for academic writing assessment

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The cluster describes a new academic paper introducing a dataset and benchmarking LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Dennis Zyska, Alla Rozovskaya, Ilia Kuznetsov, Iryna Gurevych ·

    Expos\'ia: Teaching and Assessment of Academic Writing Skills for Research Project Proposals and Peer Feedback

    arXiv:2601.06536v3 Announce Type: replace Abstract: We present Expos\'ia, the first public dataset that connects writing and feedback in higher education, enabling research on educationally grounded computational approaches to teaching and evaluating academic writing. Expos\'ia i…

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