Publications associées à Generative AI Literacy: Twelve Defining Competencies

Publications associées (18)

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

Now is an exciting time for the domain of Earth observation (EO), with a multitude of diverse sensors looking at the planet from satellites, airplanes or drones. The volume of imagery acquired is massive, and hold great potential for a variety of applicati ...

EPFL2025

A Human-Centric Approach to Explainable AI for Personalized Education

Vinitra Swamy

Deep neural networks form the backbone of artificial intelligence (AI) research, with potential to transform the human experience in areas ranging from autonomous driving to personal assistants, healthcare to education. However, their integration into the ...

EPFL2025

How to build the virtual cell with artificial intelligence: Priorities and opportunities

Charlotte Cäcilie Gertrud Bunne

Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a multi-scal ...

CELL PRESS2024

Can Generative AI Support Educators? Creating Learning Paths with PolyGloT

Tommaso Martorella

This chapter explores the intersection of generative AI and personalized learning, emphasizing the role of educators and examining the application of large language models (LLMs) in crafting personalized learning paths. The chapter examines the perception ...

Springer Nature (Switzerland)2024

Fashioning Creative Expertise with Generative AI: Graphical Interfaces for GAN-Based Design Space Exploration Beter Support Ideation Than Text Prompts for Difusion Models

Pierre Dillenbourg, Tanja Christina Käser Jacober, Richard Lee Davis, Thiemo Wambsganss, Wei Jiang

This paper investigates the potential impact of deep generative models on the work of creative professionals. We argue that current generative modeling tools lack critical features that would make them useful creativity support tools, and introduce our own ...

Association for Computing Machinery2024

Intensive Extensive: Merging Generative and Analytical Methods in Environmental Design Workflows

Christina Doumpioti

Architecture operates as an evolving interface that organises energy flows and stabilises material forms. It shapes the built environment by merging form with energy, creating spaces that resonate with occupants through sensory experiences, and by establis ...

EPFL2024

Bayesian Parameter-Efficient Fine-Tuning for Overcoming Catastrophic Forgetting

Haolin Chen

We are motivated primarily by the adaptation of text-to-speech synthesis models; however we argue that more generic parameter-efficient fine-tuning (PEFT) is an appropriate framework to do such adaptation. Nevertheless, catastrophic forgetting remains an i ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Template Inversion Attack Using Synthetic Face Images Against Real Face Recognition Systems

Hatef Otroshi Shahreza

In this paper, we use synthetic data and propose a new method for template inversion attacks against face recognition systems. We use synthetic data to train a face reconstruction model to generate high-resolution (i.e., 1024 x 1024) face images from facia ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Intentional machines: A defence of trust in medical artificial intelligence

Georg Michael Joachim Starke

Trust constitutes a fundamental strategy to deal with risks and uncertainty in complex societies. In line with the vast literature stressing the importance of trust in doctor–patient relationships, trust is therefore regularly suggested as a way of dealing ...

2022

Identifying and Classifying Urban Data Sources for Machine Learning-Based Sustainable Urban Planning and Decision Support Systems Development

Jérôme Chenal

With the increase in the amount and variety of data that are constantly produced, collected, and exchanged between systems, the efficiency and accuracy of solutions/services that use data as input may suffer if an inappropriate or inaccurate technique, met ...

MDPI2022

Misplaced Trust and Distrust: How Not to Engage with Medical Artificial Intelligence

Marcello Ienca

Artificial intelligence (AI) plays a rapidly increasing role in clinical care. Many of these systems, for instance, deep learning-based applications using multilayered Artificial Neural Nets, exhibit epistemic opacity in the sense that they preclude compre ...

CAMBRIDGE UNIV PRESS2022

Lightweight Cross-Lingual Sentence Representation Learning

Martin Jaggi, Prakhar Gupta

Large-scale models for learning fixed-dimensional cross-lingual sentence representations like LASER (Artetxe and Schwenk, 2019b) lead to significant improvement in performance on downstream tasks. However, further increases and modifications based on such ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

Learning-based Image Coding: Early Solutions Reviewing and Subjective Quality Evaluation

Touradj Ebrahimi, Pinar Akyazi

Nowadays, image and video are the data types that consume most of the resources of modern communication channels, both in fixed and wireless networks. Thus, it is vital to compress visual data as much as possible, while maintaining some target quality leve ...

SPIE-INT SOC OPTICAL ENGINEERING2021

Public Strategies for Artificial Intelligence: Which Value Drivers?

Anca-Georgiana Rusu, Gianluigi Viscusi, Marie-Valentine Renée Agnès Florin

We question the values that inform the artificial intelligence (AI) strategies developed by governments and institutions at the global level. In particular, we investigate the connection between governments? and institutions? fundamental values, second-ord ...

IEEE COMPUTER SOC2020

FeGAN: Scaling Distributed GANs

Rachid Guerraoui, Anne-Marie Kermarrec, Arsany Hany Abdelmessih Guirguis

Existing approaches to distribute Generative Adversarial Networks (GANs) either (i) fail to scale for they typically put the two components of a GAN (the generator and the discriminator) on different machines, inducing significant communication overhead, o ...

2020

Motion Prediction Using Temporal Inception Module

Pascal Fua, Mathieu Salzmann, Wei Wang, Sena Kiciroglu

Human motion prediction is a necessary component for many applications in robotics and autonomous driving. Recent methods propose using sequence-to-sequence deep learning models to tackle this problem. However, they do not focus on exploiting different tem ...

Springer, Cham2020

STC-GAN: Spatio-Temporally Coupled Generative Adversarial Networks for Predictive Scene Parsing

Jie Luo, Mengshi Qi

Predictive scene parsing is a task of assigning pixel-level semantic labels to a future frame of a video. It has many applications in vision-based artificial intelligent systems, e.g., autonomous driving and robot navigation. Although previous work has sho ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Bayesian modeling of brain function and behavior

Maya Anna Jastrzebowska

The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...

EPFL2020