Masato Taya

A hybrid framework combining CV precision with LVLM reasoning boosts damage assessment accuracy by over 2 R² points while minimizing data requirements.

Unsupervised audio-visual representation learning gets a boost from HSC-MAE, which cleverly aligns embeddings across multiple semantic levels, outperforming existing methods on weakly paired data.