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cs.HC2026

AffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition

Zheng Lian, Fan Zhang, Lan Chen +8

Open-Vocabulary Multimodal Emotion Recognition (OV-MER) aims to predict emotions without being constrained by predefined label spaces, thereby enabling fine-grained emotion underst…

cs.HC2025

EmoPrefer: Can Large Language Models Understand Human Emotion Preferences?

Zheng Lian, Licai Sun, Lan Chen +8

Descriptive Multimodal Emotion Recognition (DMER) has garnered increasing research attention. Unlike traditional discriminative paradigms that rely on predefined emotion taxonomies…

cs.HC2025

AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models

Zheng Lian, Haoyu Chen, Lan Chen +9

The emergence of multimodal large language models (MLLMs) advances multimodal emotion recognition (MER) to the next level, from naive discriminative tasks to complex emotion unders…

cs.HC2025

OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +13

Multimodal Emotion Recognition (MER) is a critical research area that seeks to decode human emotions from diverse data modalities. However, existing machine learning methods predom…

cs.HC2024

MERBench: A Unified Evaluation Benchmark for Multimodal Emotion Recognition

Zheng Lian, Licai Sun, Yong Ren +5

Multimodal emotion recognition plays a crucial role in enhancing user experience in human-computer interaction. Over the past few decades, researchers have proposed a series of alg…