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Probabilistic GCD proposals can achieve faster convergence to target distributions with fewer particles, revolutionizing how we enforce constraints in language model outputs.
By transforming LLM outputs into probabilistic programs, this approach slashes the computational cost of generating multiple code samples without sacrificing quality.
Forget LLMs, Probabilistic Circuits can now generate more realistic and diverse test inputs, boosting bug detection rates by up to 70% in SQL and XML.
