3 papers
cs.AI2025
PipeSpec: Breaking Stage Dependencies in Hierarchical LLM Decoding
Bradley McDanel, Sai Qian Zhang, Yunhai Hu +1
Speculative decoding accelerates large language model inference by using smaller draft models to generate candidate tokens for parallel verification. However, current approaches ar…
cs.CL2025
DREAM: Drafting with Refined Target Features and Entropy-Adaptive Cross-Attention Fusion for Multimodal Speculative Decoding
Yunhai Hu, Tianhua Xia, Zining Liu +6
Speculative decoding (SD) has emerged as a powerful method for accelerating autoregressive generation in large language models (LLMs), yet its integration into vision-language mode…
cs.CL2025
Speculative Decoding and Beyond: An In-Depth Survey of Techniques
Yunhai Hu, Zining Liu, Zhenyuan Dong +3
Sequential dependencies present a fundamental bottleneck in deploying large-scale autoregressive models, particularly for real-time applications. While traditional optimization app…