Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning

An innovative model interpolation-based local training technique that enhances local training across different clients through regularized model interpolation, acting as a catalyst for seamless adaptation of pre-trained models in federated learning.

Benchmarks for Corruption Invariant Person Re-Identification

The first comprehensive study establishing five ReID benchmarks for learning corruption invariant representations, providing insights on robustness of transformer vs CNN models and cross-dataset generalization.