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Achieve state-of-the-art LLM-guided program evolution for under $2, drastically cutting costs for complex optimization tasks.
Even advanced LLMs struggle to replicate human researchers' ability to find inspiring prior work, highlighting a significant gap in AI's scientific intuition.
Language models that edit their own context window like a mutable file beat external agent scaffolding across long-horizon tasks while cutting compute by up to 59%.
Personalized AI agents can achieve up to 20.9% better task success by learning from user feedback in real-time, reshaping the landscape of human-AI collaboration.
Switch Distillation not only enhances reasoning performance by up to 71% but also preserves factual recall, challenging the conventional trade-off in knowledge distillation.
