Self-Improving Language Models with Bidirectional Evolutionary Search
arXiv·medium signal
Proposes bidirectional evolutionary search as an alternative to best-of-N sampling and tree search for self-improving LLMs and agentic systems. Addresses two fundamental limitations of current search methods for both post-training data generation and inference-time scaling. Practical for builders using search-based self-improvement loops.