AI RESEARCH
DRPG (Decompose, Retrieve, Plan, Generate): An Agentic Framework for Academic Rebuttal
arXiv CS.LG
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ArXi:2601.18081v2 Announce Type: replace Despite the growing adoption of large language models (LLMs) in scientific research workflows, automated for academic rebuttal, a crucial step in academic communication and peer review, remains largely underexplored. Existing approaches typically rely on off-the-shelf LLMs or simple pipelines, which struggle with long-context understanding and often fail to produce targeted and persuasive responses.