REMOR: Automated Peer Review Generation with LLM Reasoning and Multi-Objective Reinforcement Learning

Understand

AI-based peer review systems tend to produce shallow and overpraising suggestions compared to human feedback.

• Here, we evaluate how well a reasoning LLM trained with multi-objective reinforcement learning (REMOR) can overcome these limitations.
• We start by designing a multi-aspect reward function that aligns with human evaluation of reviews.
• The aspects are related to the review itself (e.g., criticisms, novelty) and the relationship between the review and the manuscript (i.e., relevance).