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As LLMs get smarter, ditching tree search for gradient-based optimization in MLE agents unlocks significant performance gains, especially with frontier-tier models.
LLM-based agents can now automate end-to-end fine-tuning across diverse domains, but still struggle with causal reasoning, revealing both the promise and limitations of this approach.
