LLM-ABR: Designing Adaptive Bitrate Algorithms via Large Language Models
<|reference_start|>LLM-ABR: Designing Adaptive Bitrate Algorithms via Large Language Models: We present LLM-ABR, the first system that utilizes the generative capabilities of large language models (LLMs) to autonomously design adaptive bitrate (ABR) algorithms tailored for diverse network characteristics. Operating within a reinforcement learning framework, LLM-ABR empowers LLMs to design key components such as states and neural network architectures. We evaluate LLM-ABR across diverse network settings, including broadband, satellite, 4G, and 5G. LLM-ABR consistently outperforms default ABR algorithms.<|reference_end|>
@article{he2024designing,
    title={Designing Network Algorithms via Large Language Models},
    author={Zhiyuan He, Aashish Gottipati, Lili Qiu, Xufang Luo, Kenuo Xu, Yuqing
  Yang, Francis Y. Yan},
    journal={arXiv preprint arXiv:2404.01617},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.01617},
    primaryClass={cs.NI cs.LG cs.MM}
}