3 papers
cs.CL2025
Tractable Transformers for Flexible Conditional Generation
Anji Liu, Xuejie Liu, Dayuan Zhao +3
Non-autoregressive (NAR) generative models are valuable because they can handle diverse conditional generation tasks in a more principled way than their autoregressive (AR) counter…
cs.CV2025
Plug-and-Play Context Feature Reuse for Efficient Masked Generation
Xuejie Liu, Anji Liu, Guy Van den Broeck +1
Masked generative models (MGMs) have emerged as a powerful framework for image synthesis, combining parallel decoding with strong bidirectional context modeling. However, generatin…
cs.LG2025
A Tractable Inference Perspective of Offline RL
Xuejie Liu, Anji Liu, Guy Van den Broeck +1
A popular paradigm for offline Reinforcement Learning (RL) tasks is to first fit the offline trajectories to a sequence model, and then prompt the model for actions that lead to hi…