FluxFlow uses conservative flow matching with observation uncertainty and Wiener-regularized correction for ground-to-space astronomical super-resolution, outperforming baselines on real DESI-HST pairs.
POP enables context-conditioned online structural pruning of foundation models via coarse-to-fine partitioned masking without offline calibration or retraining, improving accuracy with lower latency.