NetLLM: Adapting Large Language Models for Networking

Many networking tasks now employ deep learning (DL) to solve complex prediction and optimization problems. However, current design philosophy of DL-based algorithms entails intensive engineering overhead due to the manual design of deep neural networks (DNNs) for different networking tasks. Besides, DNNs tend to achieve poor generalization performance on unseen data distributions/environments.

• NS
  National Science Foundation

  Awards: 1901466, 2313190, 2131826, 2146496, ZDSYS201707251409055
• NN
  National Natural Science Foundation of China

  Awards: ZDSYS201707251409055, 202002, 62102342, 2022QNRC001, 62293482