Showing Post From Research
Basin-wide groundwater level forecasting with Transfer Learning and LSTM
Groundwater is the lifeline of millions, but predicting its levels—especially over large areas—is very difficult. Traditional physically based models demand immense data and computational …
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U2A: Unified Unimodal Adaptation for Robust and Efficient Multimodal Learning
Imagine you are 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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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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