A multi-agent binary reward system with unbiased GRPO post-training on ICLR-320 data outperforms baselines on expert-rated novelty, feasibility, and effectiveness for scientific idea generation.
Provide thorough reasoning explaining how the methods compare on each criterion before indicating which method is superior
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Debate as Reward: A Multi-Agent Reward System for Scientific Ideation via RL Post-Training
A multi-agent binary reward system with unbiased GRPO post-training on ICLR-320 data outperforms baselines on expert-rated novelty, feasibility, and effectiveness for scientific idea generation.