Accelerating the inference of large language models (LLMs) has been a critical challenge in generative AI.Speculative decoding (SD) substantially improves LLM inference efficiency.However, its utility is limited by a fundamental constraint: the draft and target models must share the same vocabulary, thus limiting the herd of available draft models and often necessitating the training of a new model from scratch.Inspired by Dynamic Time Warping (DTW), a classic algorithm for aligning time series, we propose the algorithm TokenTiming for universal speculative decoding.It operates by re-encoding the draft token sequence to get a new target token sequence, and then uses DTW to build a mapping to transfer the probability distributions for speculative sampling.Benefiting from this, our method accommodates mismatched vocabularies and works with any off-the-shelf models without re-training and modification.We conduct comprehensive experiments on various tasks, demonstrating 1.57× speedup.This work enables a universal approach for draft model selection, making SD a more versatile and practical tool for LLM acceleration.The code is available at the link.

A motor-less fast climbing robot driven by fluid is introduced in this study. Designed with a simple five-linkage and one-piston mechanism, the robot has kinematics similar to a gecko's motion. Due to bionic design of gecko, the robot has an advantage of climbing fast on flat surfaces with any slope angles, even overhanging surfaces. Applied with fluid driven and fluidic vacuuming, the robot can carry twice extra weight as its bodyweight on vertical climbing. As a result of motor-less design, the robot owns a unique benefit to get almost all power from the pressure of fluid working medium like water, compressed air, oil and etc., regardless of little energy supplied by internal batteries for low-power control circuit and solenoid valves. Especially for home application, the robot can get power from the pressure of tap water to finish a high-rise glass window cleaning by water-washing. This robot has potential applications to cleaning, fire lighting, painting, and repairing.