A token-routing multi-modal transformer reduces inference latency by 86.2%, GPU memory by 35%, and FLOPs by 80% for beamforming tasks with negligible accuracy loss while enabling proactive handover on a real testbed dataset.
Savit: Structure-aware vision transformer pruning via co llaborative optimization
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Transformer Architecture with Minimal Inference Latency for Multi-Modal Wireless Networks
A token-routing multi-modal transformer reduces inference latency by 86.2%, GPU memory by 35%, and FLOPs by 80% for beamforming tasks with negligible accuracy loss while enabling proactive handover on a real testbed dataset.