106 citations · 119 across the 7 of their papers we have counts for
12 papers
Decoupling the Declarative from the Procedural in Vision-Language-Action Models
Nikolaos Tsagkas, Andreas Sochopoulos, Chris Xiaoxuan Lu +2
Deploying generalist robotic agents in the real world requires transferable skills. Specifically, a policy trained to clone a behavior from object-specific demonstrations must gene…
WhiFlash: Accelerating Speculative Decoding with Token-Level Cross-Paradigm Routing
Young D. Kwon, Miles Williams, Rui Li +2
The autoregressive nature of large language models (LLMs) remains a significant bottleneck for inference, particularly in complex agentic workloads. While speculative decoding (SD)…
Speculative Decoding with a Speculative Vocabulary
Miles Williams, Young D. Kwon, Rui Li +2
Speculative decoding has rapidly emerged as a leading approach for accelerating language model (LM) inference, as it offers substantial speedups while yielding identical outputs. T…
Progressive Mixed-Precision Decoding for Efficient LLM Inference
Hao Mark Chen, Fuwen Tan, Alexandros Kouris +3
In spite of the great potential of large language models (LLMs) across various tasks, their deployment on resource-constrained devices remains challenging due to their excessive co…
Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design
Hongxiang Fan, Thomas Chau, Stylianos I. Venieris +5
Attention-based neural networks have become pervasive in many AI tasks. Despite their excellent algorithmic performance, the use of the attention mechanism and feed-forward network…
Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions
Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane
DNNs are becoming less and less over-parametrised due to recent advances in efficient model design, through careful hand-crafted or NAS-based methods. Relying on the fact that not…