Papers by Hasti Seifi

3 papers
HapticCap: A Multimodal Dataset and Task for Understanding User Experience of Vibration Haptic Signals (2025.findings-emnlp)

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Challenge: a dataset of vibration haptic signals is developed to match descriptions to vibrations . a lack of large datasets annotated with textual descriptions is a challenge .
Approach: They propose a multimodal dataset and task to match user descriptions to vibration haptic signals.
Outcome: The proposed dataset matches user descriptions to vibration haptic signals . the results show that language models and audio models perform better than existing models .
UniMEEC: Towards Unified Multimodal Emotion Recognition and Emotion Cause (2024.findings-emnlp)

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Challenge: Existing studies treat emotion recognition and emotion cause extraction as two individual problems, ignoring their natural causality.
Approach: They propose a Unified Multimodal Emotion recognition and Emotion-Cause analysis framework to explore the causality between emotion and emotion cause.
Outcome: The proposed framework reformulates MERC and MECPE tasks as mask prediction problems and unifies them with a causal prompt template.
HapticLLaMA: A Multimodal Sensory Language Model for Haptic Captioning (2026.findings-eacl)

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Challenge: haptic captioning is the task of generating natural language descriptions from haptics, such as vibrations, for use in virtual reality and rehabilitation applications.
Approach: They propose a multimodal sensory language model that interprets vibration signals into descriptions in a given sensory, emotional, or associative category.
Outcome: The proposed model interprets vibration signals into descriptions in a given sensory, emotional, or associative category.

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