most citedReasoning LLMs for User-Aware Multimodal Conversational Agents

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2026

Think When It Matters: Conditional VLM Reasoning for Social Navigation with RL Policies

Ali Ahmadi, Hamed Rahimi, Adrien Jacquet Cretides +3

As mobile robots become more integrated into everyday human environments, social robot navigation is becoming essential for ensuring human comfort, safety, and trust. While reinfor…

cs.RO2026

HARMONI: Multimodal Personalization of Multi-User Human-Robot Interactions with LLMs

Jeanne Malécot, Hamed Rahimi, Jeanne Cattoni +5

Existing human-robot interaction systems often lack mechanisms for sustained personalization and dynamic adaptation in multi-user environments, limiting their effectiveness in real…

cs.AI2025

Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind

Mouad Abrini, Omri Abend, Dina Acklin +105

This volume includes a selection of papers presented at the Workshop on Advancing Artificial Intelligence through Theory of Mind held at AAAI 2025 in Philadelphia US on 3rd March 2…

cs.HC2025★ 1 cited

Reasoning LLMs for User-Aware Multimodal Conversational Agents

Hamed Rahimi, Jeanne Cattoni, Meriem Beghili +4

Personalization in social robotics is critical for fostering effective human-robot interactions, yet systems often face the cold start problem, where initial user preferences or ch…

cs.AI2025

USER-VLM 360: Personalized Vision Language Models with User-aware Tuning for Social Human-Robot Interactions

Hamed Rahimi, Adil Bahaj, Mouad Abrini +3

The integration of vision-language models into robotic systems constitutes a significant advancement in enabling machines to interact with their surroundings in a more intuitive ma…

cs.AI2025

Demographic User Modeling for Social Robotics with Multimodal Pre-trained Models

Hamed Rahimi, Mouad Abrini, Mahdi Khoramshahi +1

This paper investigates the performance of multimodal pre-trained models in user profiling tasks based on visual-linguistic demographic data. These models are critical for adapting…