Kavli Affiliate: Wei Gao| Summary:Reinforcement learning (RL) post-training of Diffusion Transformers (DiTs) is prohibitively expensive, requiring thousands of high-end GPUs. Existing works explore two directions to reduce cost: seed exploration improves training convergence by selecting high-contrast samples, yet adds compute to the critical path; spot GPUs offer 69–77% lower cost, yet sit idle during training […]
Continue.. Spotlight: Synergizing Seed Exploration and Spot GPUs for DiT RL Post-Training