Draft Verification

Draft verification accelerates large language model (LLM) decoding by initially generating a draft of the output using a faster, often smaller, model, then verifying this draft against the full LLM. Current research focuses on optimizing this verification process, exploring techniques like block-level verification to improve efficiency and employing adaptive methods that adjust to changing token probabilities. These advancements significantly reduce the computational cost of LLM inference, leading to faster generation times and broader applicability in latency-sensitive applications like real-time translation and maritime surveillance. The resulting speed improvements are crucial for deploying LLMs in resource-constrained environments and real-world scenarios.