Téo Sanchez

schoolParis-Saclay Universitybar_chart#2644 Global Rank

Total Papers

HCI Rank

#2644

Research Areas

Years Active

Recent Publications

Mental Models in Human-AI Interaction: Systematic Review of Empirical Methodologies and Guidelines

The notion of mental model has long been used in HCI to capture people's understanding and reasoning about computing systems. Eliciting users' mental models can explain their behaviors and attitudes toward a system—why and how they use, rely on, trust, or reject it. However, its use remains conceptually fragmented and…

CHI '261st AuthorGenerative AI (Text, Image, Music, Video) +3

Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine Learning

In the mid-2010s, media artists began developing practices using machine learning (ML) as an artistic medium. Since 2022, the rise of large generative models, the mainstreaming of AI as consumer products, and intensifying ethical disputes have reconfigured the conditions of their artistic practice. This paper aims to…

CC '23CorrespondingHonorable MentionGenerative AI (Text, Image, Music, Video) +1

Examining the Text-to-Image Community of Practice: Why and How do People Prompt Generative AIs?

Image generation entered the mainstream with the spread of large machine learning (ML) models capable of generating artistic images from text. AI art enthusiasts generated millions of images online within a few months, revealing the future social, economic, and legal consequences of text-to-image (TTI) generation. Th…

CSCW '211st AuthorInterpreting and Explaining AI

How do People Train a Machine? Strategies and (Mis)Understandings

Machine learning has become pervasive in modern interactive technology due to the wide range of complex tasks it can handle. However, most machine learning systems provide users with surprisingly little, if any, agency with respect to how their models are trained from data. In this paper, we explore the way people cou…

UIST '212nd AuthorHuman-LLM Collaboration +2

Marcelle: Composing Interactive Machine Learning Workflows and Interfaces

Human-centered approaches to machine learning have established theoretical foundations, design principles and interaction techniques to facilitate end-user interaction with machine learning systems. Yet, general-purpose toolkits supporting the design of interactive machine learning systems are still missing, despite t…

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