2 papers
cs.CL2026
Improving Variable-Length Generation in Diffusion Language Models via Length Regularization
Zicong Cheng, Ruixuan Jia, Jia Li +3
Diffusion Large Language Models (DLLMs) are inherently ill-suited for variable-length generation, as their inference is defined on a fixed-length canvas and implicitly assumes a kn…
cs.LG2025
DEER: Draft with Diffusion, Verify with Autoregressive Models
Zicong Cheng, Guo-Wei Yang, Jia Li +3
Efficiency, as a critical practical challenge for LLM-driven agentic and reasoning systems, is increasingly constrained by the inherent latency of autoregressive (AR) decoding. Spe…