3 citations · 6 across the 7 of their papers we have counts for
7 papers
Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models
Juntu Zhao, Junyu Deng, Yixin Ye +3
Advancements in text-to-image diffusion models have broadened extensive downstream practical applications, but such models often encounter misalignment issues between text and imag…
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
Kang You, Zekai Xu, Chen Nie +4
Spiking neural network (SNN) has attracted great attention due to its characteristic of high efficiency and accuracy. Currently, the ANN-to-SNN conversion methods can obtain ANN on…
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
Yibo Miao, Yu Lei, Feng Zhou +1
Low-shot image classification is a fundamental task in computer vision, and the emergence of large-scale vision-language models such as CLIP has greatly advanced the forefront of r…
Heterogeneous Multi-Task Gaussian Cox Processes
Feng Zhou, Quyu Kong, Zhijie Deng +3
This paper presents a novel extension of multi-task Gaussian Cox processes for modeling multiple heterogeneous correlated tasks jointly, e.g., classification and regression, via mu…
Towards Accelerated Model Training via Bayesian Data Selection
Zhijie Deng, Peng Cui, Jun Zhu
Mislabeled, duplicated, or biased data in real-world scenarios can lead to prolonged training and even hinder model convergence. Traditional solutions prioritizing easy or hard sam…
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation
Zhijie Deng, Yucen Luo
Unsupervised semantic segmentation is a long-standing challenge in computer vision with great significance. Spectral clustering is a theoretically grounded solution to it where the…