AI & ML · Oct 16
Training Reasoning Models to Generate Diverse Scientific Ideas says one best idea is the wrong target
The arXiv paper reframes scientific ideation as a grounded set problem, where quality only counts if the ideas do not clone each other.
- Evaluate research agents by portfolio quality, not the slickest single idea.
- Add duplicate detection and source grounding before ideation systems reach users.
- Treat diversity as a core reward signal, not a creativity garnish.