ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

ArXi:2604.14261v1 Announce Type: cross The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review. However, LLM-based reviewers often generate superficial, formulaic comments lacking substantive, evidence-grounded feedback. We attribute this to the underutilization of two key components of human reviewing: explicit rubrics and contextual grounding in existing work. To address this, we