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Found 3 papers, 1 papers with code
Model, Analyze, and Comprehend User Interactions and Various Attributes within a Social Media Platform
In this study, we propose a novel graph-based approach to model and analyze user interactions within a social media platform based on post-comment relationship.
Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptation
We conduct a series of experiments to highlight the missing modality robustness of our proposed method on 5 different datasets for multimodal semantic segmentation, multimodal material segmentation, and multimodal sentiment analysis tasks.
MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
Furthermore, our ablation studies also highlight the capacity of different input modalities to improve performance in the identification of different types of materials.
Ranked #1 on
Semantic Segmentation
on MCubeS (P)
