ILCB

Dyslexia in children across languages
2022-03-14 12:00 - 13:30 (Europe/Paris) | via zoom
FatimaEzzahra Benmarrakchi (UM6P – School of Collective Intelligence)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

Predicting individual differences in language learning across populations
2022-03-28 12:00 - 13:30 | via zoom
Patrick Wong (The Chinese University of Hong Kong)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-04-11 16:00 - 17:00 | via zoom
Dan Yurovsky (Carnegie Mellon University)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

Motor-vocal coordination in early language development.
2022-04-25 12:00 - 13:30 | via zoom
Eva Murillo (Universidad Autónoma de Madrid)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-05-09 12:00 - 13:30 | via zoom
Ellen Breitholtz & Christine Howes (University of Gothenburg)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-05-16 12:00 - 13:30 | via zoom
Christopher Cox (Aarhus University)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-05-23 12:00 - 13:30 | via zoom
Iris Nomikou (University of Portsmouth)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-05-30 12:00 - 13:30 | via zoom
Marlou Rasenberg (Radboud University)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-06-13 12:00 - 13:30 | via zoom
Deniz Tahiroğlu (Boğaziçi University)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-06-20 08:00 - 17:00 | via zoom
Raquel Fernández (University of Amsterdam)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

TBA
2022-07-11 08:00 - 17:00 | via zoom
Rory T. Devine (University of Birmingham)
Abstract: TBA
Where: Zoom link https://univ-amu-fr.zoom.us/j/2515421853

A Large-Scale Analysis of Human Question-Asking Strategies in a Referential Visual Search Task
2024-02-01 13:00 - 14:00
Alberto Testoni, Postdoctoral Researcher at the Institute for Logic, Language and Computation – University of Amsterdam.
Abstract:
In recent years, a multitude of datasets of human–human conversations has been released for the main purpose of training conversational agents based on data-hungry artificial neural networks. Datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on human behavior and language use. We present a method that leverages the recent development of powerful computational models to obtain the fine-grained annotation required to apply metrics and techniques from Cognitive Science to large datasets. Previous work in Cognitive Science has investigated the question-asking strategies of human participants by employing different variants of the so-called 20-question-game setting and proposing several evaluation methods. In my talk, I focus on GuessWhat, a task proposed within the Computer Vision and Natural Language Processing communities that is similar in structure to the 20-question-game setting. Crucially, the GuessWhat dataset contains tens of thousands of dialogues based on real-world images, making it a suitable setting to investigate the question-asking strategies of human players on a large scale and in a natural setting. Our results demonstrate the effectiveness of computational tools to automatically code how the hypothesis space changes throughout the dialogue in complex visual scenes. On the one hand, we confirm findings from previous work on smaller and more controlled settings. On the other hand, our analyses allow us to highlight the presence of “uninformative” questions (in terms of Expected Information Gain) at specific rounds of the dialogue. We hypothesize that these questions fulfill pragmatic constraints that human players exploit to solve visual tasks in complex scenes successfully. Our work illustrates a method that brings together efforts and findings from different disciplines to gain a better understanding of human question-asking strategies on large-scale datasets, while at the same time posing new questions about the development of conversational systems.
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