3 papers
cs.NE2024
How Biological Synapses Self-Assemble Gradient Learning
Qianli Liao, Liu Ziyin, Yulu Gan +4
Existing models of learning in the brain explain how given circuits learn, but not how biology could assemble those circuits in the first place. To address this gap, we formulate S…
cs.CL2024
On the Power of Decision Trees in Auto-Regressive Language Modeling
Yulu Gan, Tomer Galanti, Tomaso Poggio +1
Originally proposed for handling time series data, Auto-regressive Decision Trees (ARDTs) have not yet been explored for language modeling. This paper delves into both the theoreti…
cs.CV2023
Decouple Content and Motion for Conditional Image-to-Video Generation
Cuifeng Shen, Yulu Gan, Chen Chen +4
The goal of conditional image-to-video (cI2V) generation is to create a believable new video by beginning with the condition, i.e., one image and text.The previous cI2V generation…