WiSDoM: Wireless Sparse Decision Transformer with Mixture-of-Experts for Multi-Task Mobile Network Optimization

arXiv:2609.00284 · cs.NI, cs.AI, cs.LG · Submitted 2026-08-31 · Read on arXiv

cs.NI, cs.AI, cs.LG

Submitted: 2026-08-31

Updated: 2026-08-31

Terminology

• Transformer — 46× in this paper · explained in 2 episodes
• Reinforcement Learning — 14× in this paper · explained in 4 episodes
• Adaptation — 10× in this paper · explained in 1 episode
• Generalization — 9× in this paper · explained in 13 episodes
• Mixture of Experts — 8× in this paper · explained in 2 episodes
• Action Space — 7× in this paper · explained in 1 episode
• Clustering — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Quantization — 4× in this paper · explained in 12 episodes
• Data Heterogeneity — 3× in this paper · explained in 3 episodes
• Reward Function — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Explainability — 2× in this paper · explained in 3 episodes
• Federated Learning — 2× in this paper · explained in 14 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Action Masking — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Agentic Reasoning — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 5 episodes
• Edge Deployment — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Energy Efficiency — 1× in this paper · explained in 3 episodes
• Explainable AI (XAI) — 1× in this paper · explained in 7 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• In-Context Learning (ICL) — 1× in this paper · explained in 5 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Markov Decision Process — 1× in this paper
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Mobile Edge Computing — 1× in this paper · explained in 2 episodes
• Parameter Efficiency — 1× in this paper · explained in 3 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Task Decomposition — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• UAV-assisted Internet-of-Things — 1× in this paper

Sources

• Proximal Policy Optimization Algorithms
• DeepSeek-V3 Technical Report
• Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
• Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
• Mixtral of Experts

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