Apple ML Research: Self-Reflective Program Search Boosts Long-Context Performance

Jul 10, 2026

Apple ML researchers propose a self-reflective program search method to improve recursive language models (RLMs) for long-context tasks. This approach aims to select better context-interaction programs at inference time, addressing a key limitation of RLMs. The research is published on Apple's official machine learning research site.

Why it matters: This work addresses the ongoing challenge of reliable long-context reasoning in language models, which is important for many real-world applications.

Full story at: Apple Machine Learning Research ↗