Researchers have proposed a framework called ReForge that allows an ABR algorithm to adapt to changing network scenarios in real-time. The system uses a large language model (LLM) to continuously learn and improve the design of the algorithm, making small edits as needed to optimize performance. This approach was tested on nine real-world network families and showed significant improvements in quality of experience (QoE), outperforming even an oracle solution. The framework is designed to be open-sourced for further development. --- Why it matters: This matters because it could enable ABR algorithms to keep pace with the rapidly changing world, adapting to new scenarios as they arrive, rather than relying on static designs that may become outdated quickly. This has significant implications for network operators who need to optimize their services in real-time. Source: https://arxiv.org/abs/2608.15138