APRES: An Agentic Paper Revision and Evaluation System
Scientific discoveries must be communicated clearly to realize their full potential. Without effective communication, even the most groundbreaking findings risk being overlooked or misunderstood. The primary way scientists communicate their work and receive feedback from the community is through peer review. However, the current system often provides inconsistent feedback between reviewers, ultimately hindering the improvement of a manuscript and limiting its potential impact. In this paper, we introduce a novel method APRES powered by Large Language Models (LLMs) to update a scientific papers text based on an evaluation rubric. Our automated method discovers a rubric that is highly predi...
| Authors | Bingchen Zhao, Jenny Zhang, Chenxi Whitehouse et al. |
|---|---|
| Primary category | cs.CL |
| Published | 3 March 2026 |
| Last updated at source | 3 March 2026 |
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