1 citations · 1 across the 6 of their papers we have counts for
7 papers
Controlling Intent Expressiveness in Robot Motion with Diffusion Models
Wenli Shi, Clemence Grislain, Olivier Sigaud +1
Legibility of robot motion is critical in human-robot interaction, as it allows humans to quickly infer a robot's intended goal. Although traditional trajectory generation methods…
I-FailSense: Towards General Robotic Failure Detection with Vision-Language Models
Clemence Grislain, Hamed Rahimi, Olivier Sigaud +1
Language-conditioned robotic manipulation in open-world settings requires not only accurate task execution but also the ability to detect failures for robust deployment in real-wor…
Learning Longitudinal Stress Dynamics from Irregular Self-Reports via Time Embeddings
Louis Simon, Mohamed Chetouani
The widespread adoption of mobile and wearable sensing technologies has enabled continuous and personalized monitoring of affect, mood disorders, and stress. When combined with eco…
VIPER: Visual Perception and Explainable Reasoning for Sequential Decision-Making
Mohamed Salim Aissi, Clemence Grislain, Mohamed Chetouani +3
While Large Language Models (LLMs) excel at reasoning on text and Vision-Language Models (VLMs) are highly effective for visual perception, applying those models for visual instruc…
A multilingual training strategy for low resource Text to Speech
Asma Amalas, Mounir Ghogho, Mohamed Chetouani +1
Recent speech technologies have led to produce high quality synthesised speech due to recent advances in neural Text to Speech (TTS). However, such TTS models depend on extensive a…
Utility-based Adaptive Teaching Strategies using Bayesian Theory of Mind
Clémence Grislain, Hugo Caselles-Dupré, Olivier Sigaud +1
Good teachers always tailor their explanations to the learners. Cognitive scientists model this process under the rationality principle: teachers try to maximise the learner's util…
Enhancing Agent Communication and Learning through Action and Language
Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani
We introduce a novel category of GC-agents capable of functioning as both teachers and learners. Leveraging action-based demonstrations and language-based instructions, these agent…