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cs.LG2026
Learning Invariant Modality Representation for Robust Multimodal Learning from a Causal Inference Perspective
Sijie Mai, Shiqin Han
Multimodal affective computing aims to predict humans' sentiment, emotion, intention, and opinion using language, acoustic, and visual modalities. However, current models often lea…
cs.LG2026
Addressing Missing and Noisy Modalities in One Solution: Unified Modality-Quality Framework for Low-quality Multimodal Data
Sijie Mai, Shiqin Han, Haifeng Hu
Multimodal data encountered in real-world scenarios are typically of low quality, with noisy modalities and missing modalities being typical forms that severely hinder model perfor…