4 papers · 1 filter
Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance
Kai Yan, Alexander G. Schwing, Yu-Xiong Wang
Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought rollouts for many tasks such as ma…
Latent Wasserstein Adversarial Imitation Learning
Siqi Yang, Kai Yan, Alexander G. Schwing +1
Imitation Learning (IL) enables agents to mimic expert behavior by learning from demonstrations. However, traditional IL methods require large amounts of medium-to-high-quality dem…
Variational Masked Diffusion Models
Yichi Zhang, Alex Schwing, Zhizhen Zhao
Masked diffusion models have recently emerged as a flexible framework for discrete generative modeling. However, a key limitation of standard masked diffusion is its inability to e…
Towards Hierarchical Rectified Flow
Yichi Zhang, Yici Yan, Alex Schwing +1
We formulate a hierarchical rectified flow to model data distributions. It hierarchically couples multiple ordinary differential equations (ODEs) and defines a time-differentiable…