most citedFew-shot Classification via Ensemble Learning with Multi-Order Statistics

3 citations · 5 across the 7 of their papers we have counts for

collaborators

5 papers

cs.IT20242 cited

Sensing Mutual Information with Random Signals in Gaussian Channels: Bridging Sensing and Communication Metrics

Lei Xie, Fan Liu, Jiajin Luo +1

Sensing performance is typically evaluated by classical radar metrics, such as Cramer-Rao bound and signal-to-clutter-plus-noise ratio. The recent development of the integrated sen…

cs.CV2024

Few-shot Adaptation of Multi-modal Foundation Models: A Survey

Fan Liu, Tianshu Zhang, Wenwen Dai +3

Multi-modal (vision-language) models, such as CLIP, are replacing traditional supervised pre-training models (e.g., ImageNet-based pre-training) as the new generation of visual fou…

cs.CV20233 cited

Few-shot Classification via Ensemble Learning with Multi-Order Statistics

Sai Yang, Fan Liu, Delong Chen +1

Transfer learning has been widely adopted for few-shot classification. Recent studies reveal that obtaining good generalization representation of images on novel classes is the key…

cs.CV2023

Learning to Agree on Vision Attention for Visual Commonsense Reasoning

Zhenyang Li, Yangyang Guo, Kejie Wang +3

Visual Commonsense Reasoning (VCR) remains a significant yet challenging research problem in the realm of visual reasoning. A VCR model generally aims at answering a textual questi…

hep-th2023

-representations for multi-character partition functions and their -deformations

Lu-Yao Wang, V. Mishnyakov, A. Popolitov +2

In this letter we continue the development of -representations. We propose several generalizations of the known models, such as the hypergeometric Hurwitz -functions. We cons…