most citedLearning to Prompt in the Classroom to Understand AI Limits: A pilot study

8 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SI2024

Modeling Social Media Recommendation Impacts Using Academic Networks: A Graph Neural Network Approach

Sabrina Guidotti, Gregor Donabauer, Simone Somazzi +3

The widespread use of social media has highlighted potential negative impacts on society and individuals, largely driven by recommendation algorithms that shape user behavior and s…

cs.CV2024

Generalizability analysis of deep learning predictions of human brain responses to augmented and semantically novel visual stimuli

Valentyn Piskovskyi, Riccardo Chimisso, Sabrina Patania +3

The purpose of this work is to investigate the soundness and utility of a neural network-based approach as a framework for exploring the impact of image enhancement techniques on v…

q-bio.NC2023

Exploration and Comparison of Deep Learning Architectures to Predict Brain Response to Realistic Pictures

Riccardo Chimisso, Sathya Buršić, Paolo Marocco +2

We present an exploration of machine learning architectures for predicting brain responses to realistic images on occasion of the Algonauts Challenge 2023. Our research involved ex…

q-bio.NC2023

Multimodal Integration of Olfactory and Visual Processing through DCM analysis: Contextual Modulation of Facial Perception

Gianluca Rho, Alejandro Luis Callara, Francesco Bossi +5

This study examines the modulatory effect of contextual hedonic olfactory stimuli on the visual processing of neutral faces using event-related potentials (ERPs) and effective conn…

cs.HC20238 cited

Learning to Prompt in the Classroom to Understand AI Limits: A pilot study

Emily Theophilou, Cansu Koyuturk, Mona Yavari +10

Artificial intelligence's (AI) progress holds great promise in tackling pressing societal concerns such as health and climate. Large Language Models (LLM) and the derived chatbots,…

cs.RO20236 cited

World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges

Tadahiro Taniguchi, Shingo Murata, Masahiro Suzuki +8

Creating autonomous robots that can actively explore the environment, acquire knowledge and learn skills continuously is the ultimate achievement envisioned in cognitive and develo…