Xu Han

Aggressive KV cache compression can be achieved with near-zero accuracy loss by treating the cache as a trainable neural network optimized at test-time.

Deterministic forecasting embedded within generative models is unstable; DV-Flow decouples it as a parallel velocity, unlocking stable end-to-end training and superior probabilistic forecasts.