Disk Wind Feedback from High-mass Protostars. V. Application of Multi-Modal Machine Learning to Characterize Outflow Properties
This paper introduces a multi-modal deep learning framework utilizing Vision Transformers and cross-attention mechanisms to accurately infer protostellar mass, inclination, and position angle from CO observations, effectively overcoming projection biases and demonstrating superior robustness compared to traditional convolutional networks.