Token-Oriented Semantic Communication with Pretrained Vision Transformers

arXiv:2608.25410 · eess.SP, cs.AI, cs.CV, cs.LG · Submitted 2026-08-26 · Read on arXiv

eess.SP, cs.AI, cs.CV, cs.LG

Submitted: 2026-08-26

Updated: 2026-09-08

Terminology

• Accuracy — 60× in this paper · explained in 1 episode
• Transformer — 33× in this paper · explained in 2 episodes
• Latent Representation — 16× in this paper · explained in 2 episodes
• Latent Representations — 12× in this paper · explained in 3 episodes
• Adaptation — 9× in this paper · explained in 1 episode
• Embeddings — 6× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Robustness — 5× in this paper · explained in 5 episodes
• Modularity — 3× in this paper · explained in 9 episodes
• Quantization — 3× in this paper · explained in 12 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Edge Devices — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation Studies — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Edge AI — 1× in this paper · explained in 2 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

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