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cs.LG2026
Backpropagating Verifier Rewards Through Continuous Flow Language Models
Xu Han, Jiajing Hu, Li-Ping Liu
Reinforcement learning (RL) has substantially improved the reasoning of autoregressive and discrete-diffusion language models. Language models that generate continuous token embedd…
cs.LG2026
Deterministic Prediction as Global Velocity: Flow Matching for Probabilistic Time-Series Forecast
Jiajing Hu, Xu Han, Li-Ping Liu
Accurate uncertainty quantification is critical for many time series forecasting applications, and recent studies have increasingly adopted generative models to capture predictive…
cs.CV2026
Self-Consistent Flow: Unifying Velocity and Endpoint Prediction for Rectified Flow Models
Xu Han, Jiajing Hu, Li-Ping Liu
In rectified-flow-based generative models, the neural network can be trained to predict two different targets, such as the instantaneous velocity or the data endpoint, to perform d…