Teachers, Take Care of the Essential. the Rest Is Story: Using LLM and Social Robots for Content Approaching by Storytelling

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We introduce DiscoDiff, a text-to-music generative model that utilizes two latent diffusion models to produce high-fidelity 44.1kHz music hierarchically. Our approach significantly enhances audio quality through a coarse-to-fine generation strategy, levera ...

Fluent human-robot interactions are essential for robots to be accepted and used in social scenarios including education, healthcare, or entertainment. Foundation models and Large Language Models (LLMs) in particular facilitate natural generation of text i ...

We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domestic and frequent therapies. We build a supervised approach using information ...

To protect both local gradients and estimated parameters in distributed learning, this paper introduces a masked diffusion (MD) strategy, leading to two algorithms: the MD stochastic gradient (MD-SG) and the MD primal-dual stochastic gradient (MPD-SG). The ...

Virtual reality (VR) technology revitalises rehabilitation training by creating rich, interactive virtual rehabilitation scenes and tasks that deeply engage patients. Robotics with immersive VR environments have the potential to significantly enhance the s ...

The social learning paradigm for distributed hypothesis testing involves a collection of agents interacting over a graph, each observing streaming data that provide evidence about the state of the environment. These agents perform a series of local Bayesia ...

Being able to deliver feedback to peers is a key management skill and something engineering students report finding difficult, due to the relational and emotional implications. This experiential activity provides students with emotional management strategi ...

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that ar ...

Transformer-based architectures are the model of choice for natural language understanding, but they come at a significant cost, as they have quadratic complexity in the input length, require a lot of training data, and can be difficult to tune. In the pur ...

Human-object interaction is of great relevance for robots to operate in human environments. However, state-of-the-art robotic hands are far from replicating humans skills. It is, therefore, essential to study how humans use their hands to develop similar r ...

We develop here a novel hypothesis that may generate a general research framework of how autonomous robots may act as a future contingency to counteract the ongoing ecological mass extinction process. We showcase several research projects that have underta ...

Teachers, Take Care of the Essential. the Rest Is Story: Using LLM and Social Robots for Content Approaching by Storytelling

Chattez avec Graph Search

Coarse-to-Fine Text-to-Music Latent Diffusion

Improving the Fluency of Robot-Human Interaction Through Embodied Expression of Emotion via Foundation Models

Learning Hand State Estimation for a Light Exoskeleton

Masked Diffusion Strategy for Privacy-Preserving Distributed Learning

Rehabilitation exoskeleton system with bidirectional virtual reality feedback training strategy

Inverse Graph Learning from Social Interactions

How to Support Students Giving Each Other Constructive Feedback, Especially When It Is Difficult to Hear

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks

HyperMixer: An MLP-based Low Cost Alternative to Transformers

Hand-Object Interaction: From Human Demonstrations to Robot Manipulation

Social Integrating Robots Suggest Mitigation Strategies for Ecosystem Decay