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Testoni A, Bernardi R, Ruggeri A. The Efficiency of Question-Asking Strategies in a Real-World Visual Search Task. Cogn Sci 2023; 47:e13396. [PMID: 38142430 DOI: 10.1111/cogs.13396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 11/14/2023] [Accepted: 12/01/2023] [Indexed: 12/26/2023]
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. In this paper, we argue that 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 our work, we 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 are exploited by human players 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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Affiliation(s)
- Alberto Testoni
- Institute for Logic, Language and Computation (ILLC), University of Amsterdam
| | - Raffaella Bernardi
- Center for Mind/Brain Sciences (CIMeC), University of Trento
- Department of Information Engineering and Computer Science (DISI), University of Trento
| | - Azzurra Ruggeri
- MPRG iSearch, Max Planck Institute for Human Development, Berlin
- School of Social Sciences and Technology, Technical University Munich
- Department of Cognitive Science, Central European University
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Testoni A, Greco C, Bernardi R. Artificial Intelligence Models Do Not Ground Negation, Humans Do. GuessWhat?! Dialogues as a Case Study. Front Big Data 2022; 4:736709. [PMID: 35141519 PMCID: PMC8819179 DOI: 10.3389/fdata.2021.736709] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Abstract
Negation is widely present in human communication, yet it is largely neglected in the research on conversational agents based on neural network architectures. Cognitive studies show that a supportive visual context makes the processing of negation easier. We take GuessWhat?!, a referential visually grounded guessing game, as test-bed and evaluate to which extent guessers based on pre-trained language models profit from negatively answered polar questions. Moreover, to get a better grasp of models' results, we select a controlled sample of games and run a crowdsourcing experiment with subjects. We evaluate models and humans against the same settings and use the comparison to better interpret the models' results. We show that while humans profit from negatively answered questions to solve the task, models struggle in grounding negation, and some of them barely use it; however, when the language signal is poorly informative, visual features help encoding the negative information. Finally, the experiments with human subjects put us in the position of comparing humans and models' predictions and get a grasp about which models make errors that are more human-like and as such more plausible.
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Affiliation(s)
- Alberto Testoni
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
- *Correspondence: Alberto Testoni
| | - Claudio Greco
- Centre for Mind and Brain Sciences, University of Trento, Trento, Italy
| | - Raffaella Bernardi
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
- Centre for Mind and Brain Sciences, University of Trento, Trento, Italy
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Bhandari P, Longcroft-Wheaton G, Libanio D, Pimentel-Nunes P, Albeniz E, Pioche M, Sidhu R, Spada C, Anderloni A, Repici A, Haidry R, Barthet M, Neumann H, Antonelli G, Testoni A, Ponchon T, Siersema PD, Fuccio L, Hassan C, Dinis-Ribeiro M. Revising the European Society of Gastrointestinal Endoscopy (ESGE) research priorities: a research progress update. Endoscopy 2021; 53:535-554. [PMID: 33822332 DOI: 10.1055/a-1397-3005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND One of the aims of the European Society of Gastrointestinal Endoscopy (ESGE) is to encourage high quality endoscopic research at a European level. In 2016, the ESGE research committee published a set of research priorities. As endoscopic research is flourishing, we aimed to review the literature and determine whether endoscopic research over the last 4 years had managed to address any of our previously published priorities. METHODS As the previously published priorities were grouped under seven different domains, a working party with at least two European experts was created for each domain to review all the priorities under that domain. A structured review form was developed to standardize the review process. The group conducted an extensive literature search relevant to each of the priorities and then graded the priorities into three categories: (1) no longer a priority (well-designed trial, incorporated in national/international guidelines or adopted in routine clinical practice); (2) remains a priority (i. e. the above criterion was not met); (3) redefine the existing priority (i. e. the priority was too vague with the research question not clearly defined). RESULTS The previous ESGE research priorities document published in 2016 had 26 research priorities under seven domains. Our review of these priorities has resulted in seven priorities being removed from the list, one priority being partially removed, another seven being redefined to make them more precise, with eleven priorities remaining unchanged. This is a reflection of a rapid surge in endoscopic research, resulting in 27 % of research questions having already been answered and another 27 % requiring redefinition. CONCLUSIONS Our extensive review process has led to the removal of seven research priorities from the previous (2016) list, leaving 19 research priorities that have been redefined to make them more precise and relevant for researchers and funding bodies to target.
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Affiliation(s)
- Pradeep Bhandari
- Department of Gastroenterology, Portsmouth University Hospital NHS Trust, Portsmouth, UK
| | | | - Diogo Libanio
- Gastroenterology Department, Portuguese Oncology Institute of Porto, Porto, Portugal.,Center for Research in Health Technologies and Information Systems (CINTESIS), Faculty of Medicine, Porto, Portugal
| | - Pedro Pimentel-Nunes
- Gastroenterology Department, Portuguese Oncology Institute of Porto, Porto, Portugal.,Center for Research in Health Technologies and Information Systems (CINTESIS), Faculty of Medicine, Porto, Portugal
| | - Eduardo Albeniz
- Gastroenterology Department, Endoscopy Unit, Complejo Hospitalario de Navarra, Navarrabiomed-UPNA-IdiSNA, Pamplona, Spain
| | - Mathieu Pioche
- Gastroenterology Division, Edouard Herriot Hospital, Lyon, France
| | - Reena Sidhu
- Academic Department of Gastroenterology, Royal Hallamshire Hospital, Sheffield, UK
| | - Cristiano Spada
- Digestive Endoscopy and Gastroenterology, Fondazione Poliambulanza, Brescia, Italy.,Università Cattolica del Sacro Cuore, Rome, Italy
| | - Andrea Anderloni
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli, Ariccia, Rome, Italy
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Milan, Italy.,Digestive Endoscopy Unit, IRCSS Humanitas Research Hospital, Milan, Italy
| | - Rehan Haidry
- Department of Gastroenterology, University College London Hospitals, London, UK
| | - Marc Barthet
- Department of Gastroenterology, Hôpital Nord, Assistance publique des hôpitaux de Marseille, Marseille, France
| | - Helmut Neumann
- Department of Medicine I, University Medical Center Mainz, Mainz, Germany.,GastroZentrum Lippe, Bad Salzuflen, Germany
| | - Giulio Antonelli
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli, Ariccia, Rome, Italy.,Nuovo Regina Margherita Hospital, Rome, Italy.,Department of Translational and Precision Medicine, "Sapienza" University of Rome, Rome, Italy
| | | | - Thierry Ponchon
- Gastroenterology Division, Edouard Herriot Hospital, Lyon, France
| | - Peter D Siersema
- Department of Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Lorenzo Fuccio
- Department of Medical and Surgical Sciences, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | | | - Mario Dinis-Ribeiro
- Gastroenterology Department, Portuguese Oncology Institute of Porto, Porto, Portugal.,Center for Research in Health Technologies and Information Systems (CINTESIS), Faculty of Medicine, Porto, Portugal
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