RobotEQ is a new benchmark dataset and evaluation suite showing that current embodied AI models fall short on active social-norm compliance, especially spatial grounding, though RAG with external knowledge helps.
Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph
3 Pith papers cite this work. Polarity classification is still indexing.
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AffectGPT-RL applies reinforcement learning to optimize non-differentiable emotion wheel metrics in open-vocabulary multimodal emotion recognition, yielding performance gains and state-of-the-art results on basic emotion recognition benchmarks.
SHREC is a new benchmark dataset of embodied human-robot conversations that shows substantial performance gaps in state-of-the-art foundation models on tasks involving social error detection and rationale generation.
citing papers explorer
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RobotEQ: Transitioning from Passive Intelligence to Active Intelligence in Embodied AI
RobotEQ is a new benchmark dataset and evaluation suite showing that current embodied AI models fall short on active social-norm compliance, especially spatial grounding, though RAG with external knowledge helps.
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AffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition
AffectGPT-RL applies reinforcement learning to optimize non-differentiable emotion wheel metrics in open-vocabulary multimodal emotion recognition, yielding performance gains and state-of-the-art results on basic emotion recognition benchmarks.
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Social Human Robot Embodied Conversation (SHREC) Dataset: Benchmarking Foundational Models' Social Reasoning
SHREC is a new benchmark dataset of embodied human-robot conversations that shows substantial performance gaps in state-of-the-art foundation models on tasks involving social error detection and rationale generation.