3 papers
cs.CL2026
Improving Diffusion Language Model Decoding through Joint Search in Generation Order and Token Space
Yangyi Shen, Tianjian Feng, Jiaqi Han +5
Diffusion Language Models (DLMs) offer order-agnostic generation that can explore many possible decoding trajectories. However, current decoding methods commit to a single trajecto…
cs.AI2026
BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decoding
Ziyi Zhao, Jinzhao Zhou, Xiaowei Jiang +6
Decoding linguistic information from electroencephalography (EEG) remains challenging due to the brain's distributed and nonlinear organization. We present BrainStack, a functional…
cs.CL2025
Time Is a Feature: Exploiting Temporal Dynamics in Diffusion Language Models
Wen Wang, Bozhen Fang, Chenchen Jing +6
Diffusion large language models (dLLMs) generate text through iterative denoising, yet current decoding strategies discard rich intermediate predictions in favor of the final outpu…