7 papers · 1 filter
Multimodal Classification via Total Correlation Maximization
Feng Yu, Xiangyu Wu, Yang Yang +1
Multimodal learning integrates data from diverse sensors to effectively harness information from different modalities. However, recent studies reveal that joint learning often over…
Adaptive Debiasing Tsallis Entropy for Test-Time Adaptation
Xiangyu Wu, Dongming Jiang, Feng Yu +5
Mainstream Test-Time Adaptation (TTA) methods for adapting vision-language models, e.g., CLIP, typically rely on Shannon Entropy (SE) at test time to measure prediction uncertainty…
Text as Any-Modality for Zero-Shot Classification by Consistent Prompt Tuning
Xiangyu Wu, Feng Yu, Yang Yang +1
The integration of prompt tuning with multimodal learning has shown significant generalization abilities for various downstream tasks. Despite advancements, existing methods heavil…
Multi-Label Test-Time Adaptation with Bound Entropy Minimization
Xiangyu Wu, Feng Yu, Qing-Guo Chen +2
Mainstream test-time adaptation (TTA) techniques endeavor to mitigate distribution shifts via entropy minimization for multi-class classification, inherently increasing the probabi…
Second Place Solution of WSDM2023 Toloka Visual Question Answering Challenge
Xiangyu Wu, Zhouyang Chi, Yang Yang +1
In this paper, we present our solution for the WSDM2023 Toloka Visual Question Answering Challenge. Inspired by the application of multimodal pre-trained models to various downstre…
The Solution for the CVPR2023 NICE Image Captioning Challenge
Xiangyu Wu, Yi Gao, Hailiang Zhang +3
In this paper, we present our solution to the New frontiers for Zero-shot Image Captioning Challenge. Different from the traditional image captioning datasets, this challenge inclu…