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cs.LG2026
Fluid-DiT: Graph-Free Diffusion Transformers for Fluid Flow Simulations Learning
Shentong Mo, Guolin Ke
Simulating complex fluid flows requires capturing full equilibrium distributions rather than just mean trajectories, yet high-fidelity solvers remain computationally prohibitive. R…
cs.LG2026
Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning
Shentong Mo
Designing effective reward functions is a cornerstone of reinforcement learning (RL), yet it remains a challenging and labor-intensive process due to the inefficiencies and inconsi…