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20212026
most citedMultimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal Representations

167 citations · 215 across the 22 of their papers we have counts for

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5 papers · 1 filter

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

MissMAC-Bench: Building Solid Benchmark for Missing Modality Issue in Robust Multimodal Affective Computing

Ronghao Lin, Honghao Lu, Ruixing Wu +5

Current Multimodal Affective Computing (MAC) systems heavily rely on the completeness of multiple modalities to accurately understand human's affective state. However, in real-worl…

cs.AI2025

E3RG: Building Explicit Emotion-driven Empathetic Response Generation System with Multimodal Large Language Model

Ronghao Lin, Shuai Shen, Weipeng Hu +5

Multimodal Empathetic Response Generation (MERG) is crucial for building emotionally intelligent human-computer interactions. Although large language models (LLMs) have improved te…

cs.AI2021★ 5 cited

Maximum Entropy Population-Based Training for Zero-Shot Human-AI Coordination

Rui Zhao, Jinming Song, Yufeng Yuan +5

We study the problem of training a Reinforcement Learning (RL) agent that is collaborative with humans without using any human data. Although such agents can be obtained through se…

cs.AI2021★ 13 cited

Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysis

Sijie Mai, Ying Zeng, Shuangjia Zheng +1

The wide application of smart devices enables the availability of multimodal data, which can be utilized in many tasks. In the field of multimodal sentiment analysis (MSA), most pr…