10 papers
RobotEQ: Transitioning from Passive Intelligence to Active Intelligence in Embodied AI
Kuofei Fang, Xinyi Che, Haomin Ouyang +12
Embodied AI is a prominent research topic in both academia and industry. Current research centers on completing tasks based on explicit user instructions. However, for robots to in…
MOTOR-Bench: A Real-world Dataset and Multi-agent Framework for Zero-shot Human Mental State Understanding
Xiaoyu Yuan, Niklas Heikkala, Tiina Törmänen +3
Understanding human mental states from natural behavior is crucial for intelligent systems in the real world. However, most current research focuses on predicting isolated mental s…
SayNext-Bench: Why Do LLMs Struggle with Next-Utterance Anticipation?
Yueyi Yang, Haotian Liu, Fang Kang +4
We explore the use of large language models (LLMs) for next-utterance anticipation in human dialogue. Despite recent advances in LLMs demonstrating their ability to engage in natur…
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…
iMiGUE-Speech: A Spontaneous Speech Dataset for Affective Analysis
Sofoklis Kakouros, Fang Kang, Haoyu Chen
This work presents iMiGUE-Speech, an extension of the iMiGUE dataset that provides a spontaneous affective corpus for studying emotional and affective states. The new release focus…
AffectGPT-R1: Leveraging Reinforcement Learning for Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Fan Zhang, Yazhou Zhang +5
Open-Vocabulary Multimodal Emotion Recognition (OV-MER) aims to predict emotions without being constrained by label spaces, enabling fine-grained emotion understanding. Unlike trad…