First dedicated survey organizing diffusion and flow matching models for tabular data synthesis, imputation, anomaly detection, and related tasks, covering literature from 2015 to 2026 and highlighting open problems.
Attention is all you need
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A lightweight Transformer predicts MCS success probabilities for 5G MBS on commercial 0.5 ms slot data using an asymmetric safety loss, reaching 86.89% reliability versus 31.65% for throughput-focused baselines.
Integrating foot position maps into heightmaps and adding a locomotion-stability reward in an attention-based RL framework improves quadrupedal success rates on both trained and out-of-domain complex terrains.
Time-series Vision Transformer reconstructs cloud-covered multispectral imagery by integrating temporal coherence and SAR data via attention, outperforming non-time-series and SAR-free baselines.
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Diffusion and Flow Matching Models for Tabular Data: A Survey
First dedicated survey organizing diffusion and flow matching models for tabular data synthesis, imputation, anomaly detection, and related tasks, covering literature from 2015 to 2026 and highlighting open problems.
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Transformer-Based MCS Prediction for 5G Multicast-Broadcast Services (MBS)
A lightweight Transformer predicts MCS success probabilities for 5G MBS on commercial 0.5 ms slot data using an asymmetric safety loss, reaching 86.89% reliability versus 31.65% for throughput-focused baselines.
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Learning Locomotion on Complex Terrain for Quadrupedal Robots with Foot Position Maps and Stability Rewards
Integrating foot position maps into heightmaps and adding a locomotion-stability reward in an attention-based RL framework improves quadrupedal success rates on both trained and out-of-domain complex terrains.
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Vision Transformer-Based Time-Series Image Reconstruction for Cloud-Filling Applications
Time-series Vision Transformer reconstructs cloud-covered multispectral imagery by integrating temporal coherence and SAR data via attention, outperforming non-time-series and SAR-free baselines.