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cs.AI2026
Uncovering Latent Depression Severity for Binary Depression Detection via Advantage-weighting Ranking
Manning Gao, Tingyi Liu, Leheng Zhang +3
Automatic depression detection using audio-visual data faces significant challenges, particularly in disentangling overlapping feature distributions and establishing robust decisio…
cs.AI2026
A Conflict-Aware Penalty and Statistical Loss Framework for Balancing Modalities and Enhancing Stability in Multimodal Sentiment Analysis
Jianheng Dai, Jiazhang Liang, Sijie Mai
Multimodal Sentiment Analysis (MSA) fuses text, acoustic, and visual streams to infer sentiment. Because pre-trained text encoders are far more expressive than their acoustic and v…
cs.AI2025
Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting
Miaosen Luo, Jiesen Long, Zequn Li +3
Multimodal Affective Computing (MAC) aims to recognize and interpret human emotions by integrating information from diverse modalities such as text, video, and audio. Recent advanc…