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New dataset captures end-to-end scholarly writing process

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced ScholaWrite, a novel dataset designed to capture the complete scholarly writing process. This dataset was collected using a Chrome extension that recorded keystrokes within Overleaf, documenting the multi-month journey from initial drafts to final manuscripts for five computer science preprints. The data includes over 62,000 text changes and provides insights into the cognitive demands and task-switching involved in academic writing, highlighting current limitations of LLMs in assisting this process. AI

IMPACT Provides data to develop more effective AI writing assistants that understand the cognitive process of authors.

RANK_REASON The cluster describes a new dataset for scholarly writing research, including a paper and associated data/code resources. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.CL →

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

New dataset captures end-to-end scholarly writing process

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The cluster describes a new dataset for scholarly writing research, including a paper and associated data/code resources. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Khanh Chi Le, Linghe Wang, Minhwa Lee, Ross Volkov, Luan Tuyen Chau, Dongyeop Kang ·

    ScholaWrite: A Dataset of End-to-End Scholarly Writing Process

    arXiv:2502.02904v5 Announce Type: replace-cross Abstract: Writing is a cognitively demanding activity that requires constant decision-making, heavy reliance on working memory, and frequent shifts between tasks of different goals. To build writing assistants that truly align with …

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