Anchorless Diversification for Parallel LLM Ideation 事件

Anchorless Diversification for Parallel LLM Ideation arXiv:2605.30150v1 Announce Type: new Abstract: LLMs are increasingly used to generate candidate-idea pools for creative tasks where broad exploration is valuable. Parallel inference can be attractive in this setting when it broadens the pool while retaining quality and cost efficiency. We study inference-time controls for candidate-pool diversification, asking whether anchorless methods can rival methods that depend on observed seed ideas. A