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September 24, 2025Open Access

A Multi-Task Evaluation of LLMs' Processing of Academic Text Input

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Authors

TLTianyi LiYQYu QinOSOlivia R. Liu Sheng

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Overview

Evaluation demonstrates limited performance of large language models in academic text processing, suggesting caution in peer review applications.

Key Points

  • LLMs' performance in processing academic texts shows significant limitations and inconsistencies.
  • In assessments, Google's Gemini model struggled with grading text and providing qualitative insights despite some strengths.
  • Robust evaluations included linguistic assessments, comparisons to ground truth, and human evaluations, revealing flaws.
  • Overall findings advise against unchecked use of LLMs for generating peer reviews in academic contexts.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68d6e16f8b2b6861e4c4016bhttps://doi.org/10.48550/arxiv.2508.11779
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