Asia
Synergistic Dual Spatial-aware Generation of Image-to-Text and Text-to-Image Y u Zhao
In the visual spatial understanding (VSU) area, spatial image-to-text (SI2T) and spatial text-to-image (ST2I) are two fundamental tasks that appear in dual form. Existing methods for standalone SI2T or ST2I perform imperfectly in spatial understanding, due to the difficulty of 3D-wise spatial feature modeling.
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Our code is available at https://github.com/sail-sg/stde
Zipfian Whitening
The word embedding space in neural models is skewed, and correcting this can improve task performance.
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
By introducing LLM-embedded textual timestamps, Auto-Times can utilize chronological information to align multivariate time series. Empirically, AutoTimes achieves state-of-the-art with 0.1% trainable parameters and
EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models
Our experiments with extensive data indicate that the model trained on generated data of the advanced model can approximate its generation capability. However, it requires large-scale samples of 10 million or more.