Architecture Search Framework for Inference-Time Techniques

introduces a modular framework for building and optimizing LLMs by combining multiple inference-time techniques; this approach reframes the challenge of LLM system design as a hyperparameter optimization problem; tested on benchmarks including MT-Bench and CodeContests, Archon surpasses leading models such as GPT-4o and Claude 3.5 Sonnet, achieving a 15.1% average accuracy improvement.