hexo-ai/sia

原文摘要

SIA is a Self Improving AI framework to autonomously improve the performance of any AI system (Model / Agent) on a benchmark task. SIA (Self-Improving AI) Official implementation of SIA: Self Improving AI with Harness & Weight Updates (Hebbar et al., 2026) — a self-improving loop where a language-model agent updates both the harness and the weights of a task-specific agent. The paper reports a 56.6% gain on LawBench, 91.9% runtime reduction on GPU kernels, and 502% improvement on single-cell RNA denoising over baseline. SIA is a Self Improving AI framework to autonomously improve the performance of any AI system (Model / Agent) on a benchmark task. Just want to try it? Skip to Run SIA locally . Introduction Videos SIA setup SIA Runs Visualizer Architecture Control flow between Meta, Target, and Feedback agents over successive generations. SIA operates by coordinating three main types of AI agents that work together to continuously improve task performance: Glossary Meta-Agent : Reads the task description and generates an initial Target Agent tailored to the task. Target / Task Specific Agent : Attempts to complete the task and records its actions and results. Feedback/Improvement A…