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REFLEX decouples vision and code generation in evolutionary policy search

A new framework separates visual diagnosis from code synthesis to make LLM-guided policy evolution more auditable and sample-efficient, solving control tasks in under 10 model calls.

1 min read

Researchers have released REFLEX, a train-free evolutionary framework that restructures how large language models guide the search for interpretable programmatic policies. Rather than asking a single model to both diagnose behavioral problems and generate corrective code in one call, REFLEX splits t...

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Method & sources
Source type
Primary publication (lab/vendor blog) — our analysis + implication
Source link
r/arxiv-compression
Published
UTC
Byline
By the gotcontext.ai team (editorial standards)
Correction?
corrections@gotcontext.ai

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