Ghazaleh Khodabandelou — accepted AI-conference papers

2025

Hyperbolic Transformers with LLMs for Multimodal Human Activity Recognition

Farnaz Soleimani, Ghazaleh Khodabandelou, Abdelghani Chibani, Yacine Amirat

IROS 2025

Human Activity Recognition (HAR) plays a crucial role in applications such as healthcare, smart environments, and human-robot interaction. This study proposes a novel Hyperbolic optimization strategy to improve model generalization by leveraging the geometric structure of the parameter space. To eva

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2025

Multimodal Human Activity Recognition with a Large Language Model for Enhanced Human-Robot Interaction

Ghazaleh Khodabandelou, Abdelghani Chibani, Yacine Amirat

IROS 2025

This paper presents a novel framework for Human Activity Recognition (HAR) by unifying all sensor streams, visual, audio, and inertial, into a single textual domain, enabling the direct application of GPT-3 for multimodal data classification. Unlike traditional pipelines that use dedicated encoders

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