Yanhua Jiao — accepted AI-conference papers

2026

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding

Yanhua Jiao, Tianyi Wu, Xiaoxi Sun, Yulin Li, Huiling Zhen, Libo Qin +3

ICML 2026poster

While parallel decoding is central to the efficiency of Diffusion Large Language Models (dLLMs), current strategies are often hindered by overly conservative confidence thresholds. These thresholds, necessitated by the Joint Probability Dependence Error (JPDE), result in redundant denoising iteratio…

Cited by 0 Source ↗Scholar ↗

2026

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM

Tianyi Wu, Xiaoxi Sun, Yanhua Jiao, Yulin Li, Yixin Chen, Yun-Hao Cao +2

ICLR 2026poster

Diffusion Large Language Models (dLLMs) offer a promising alternative to autoregressive models, excelling in text generation tasks due to their bidirectional attention mechanisms. However, their computational complexity, scaling as $\mathcal{O}(L^3)$ with sequence length $L$, poses significant chall…

Cited by 0 Source ↗code ↗Scholar ↗