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U2A: Unified Unimodal Adaptation for Robust and Efficient Multimodal Learning
Imagine you’re using an AI system that analyzes both images and text to classify food items. It works great—until suddenly, the text data is missing.
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Model, Analyze, and Comprehend User Interactions within a Social Media Platform
Social media has transformed how we communicate, but have you ever wondered what really happens beneath the surface? Who drives the discussions?
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Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation
Missing modalities at test time can cause significant degradation in the performance of multimodal systems. In this paper, we presented a simple and parameter-efficient adaptation method for …
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MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection
In real-world applications, input modalities might be missing due to factors like sensor malfunctions or data constraints. Our recent paper addresses this challenge with a method called …
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MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
Leveraging information across diverse modalities is known to enhance performance on multimodal segmentation tasks. However, effectively fusing information from different modalities remains …
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