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20242026
most citedAffectGPT: Dataset and Framework for Explainable Multimodal Emotion Recognition

2 citations · 2 across the 3 of their papers we have counts for

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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.HC20252 cited

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.HC20241 cited

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.HC20242 cited

AffectGPT: Dataset and Framework for Explainable Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +3

Explainable Multimodal Emotion Recognition (EMER) is an emerging task that aims to achieve reliable and accurate emotion recognition. However, due to the high annotation cost, the…

cs.HC20246 cited

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…