Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Ledrou-Paquet, V.; Fiset, D.; Carré, M.; Guérette, J.; Blais, C.
The facial information underlying economic decision-making Article de journal
Dans: Perception, vol. 55, no 3, p. 243–265, 2026, ISSN: 03010066 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Bubbles, face evaluation, face perception, facial trustworthiness, Social Perception, trust game, trustworthiness
@article{ledrou-paquet_facial_2026,
title = {The facial information underlying economic decision-making},
author = {V. Ledrou-Paquet and D. Fiset and M. Carré and J. Guérette and C. Blais},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105020458633&doi=10.1177%2F03010066251387848&partnerID=40&md5=7c1ead96fa13944073ed63bc952ca723},
doi = {10.1177/03010066251387848},
issn = {03010066 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Perception},
volume = {55},
number = {3},
pages = {243–265},
abstract = {Faces are rapidly and automatically assessed on multiple social dimensions, including trustworthiness. The high inter-rater agreement on this social judgment suggests a systematic association between facial appearance and perceived trustworthiness. The facial information used by observers during explicit trustworthiness judgments has been studied before. However, it remains unknown whether the same perceptual strategies are used during decisions that involve trusting another individual, without necessitating an explicit trustworthiness judgment. To explore this, 53 participants completed the Trust Game, an economic decision task, while facial information was randomly sampled using the Bubbles method. Our results show that economic decisions based on facial cues rely on similar visual information as that used during explicit trustworthiness judgments. We then manipulated facial features identified as diagnostic for trust to test their influence on perceived trustworthiness (Experiment 2) and on trust-related behaviors (Experiment 3). Across all experiments, subtle, targeted changes to facial features systematically shifted both impressions and monetary trust decisions. These findings demonstrate that the same perceptual strategies underlie explicit judgments and trust behaviors, highlighting the applied relevance of even minimal alterations in facial appearance. These findings should be replicated with real faces from diverse demographic backgrounds to confirm their generalizability. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).},
keywords = {Bubbles, face evaluation, face perception, facial trustworthiness, Social Perception, trust game, trustworthiness},
pubstate = {published},
tppubtype = {article}
}
Faces are rapidly and automatically assessed on multiple social dimensions, including trustworthiness. The high inter-rater agreement on this social judgment suggests a systematic association between facial appearance and perceived trustworthiness. The facial information used by observers during explicit trustworthiness judgments has been studied before. However, it remains unknown whether the same perceptual strategies are used during decisions that involve trusting another individual, without necessitating an explicit trustworthiness judgment. To explore this, 53 participants completed the Trust Game, an economic decision task, while facial information was randomly sampled using the Bubbles method. Our results show that economic decisions based on facial cues rely on similar visual information as that used during explicit trustworthiness judgments. We then manipulated facial features identified as diagnostic for trust to test their influence on perceived trustworthiness (Experiment 2) and on trust-related behaviors (Experiment 3). Across all experiments, subtle, targeted changes to facial features systematically shifted both impressions and monetary trust decisions. These findings demonstrate that the same perceptual strategies underlie explicit judgments and trust behaviors, highlighting the applied relevance of even minimal alterations in facial appearance. These findings should be replicated with real faces from diverse demographic backgrounds to confirm their generalizability. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
2.
Elhajjout, A.; Houda, Z. A. E.; Moudoud, H.; Brik, B.; Jan, M. A.
Federated Large Language Models for A Trustworthy and Privacy-Preserving Healthcare: Applications, Challenges, and Future Research Directions Article de journal
Dans: IEEE Journal of Biomedical and Health Informatics, 2026, ISSN: 21682194 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Application research, Artificial intelligence, digital health, Distributed computer systems, Federated learning, Fine tuning, Health care, Health care application, Healthcare AI, human, Internet, Internet of medical thing, Internet of Medical Things, Language model, Large language model, large language models, Learning systems, male, Medical computing, natural language processing, Parameter-efficient fine-tuning, patient coding, Privacy, Privacy preservation, Privacy preserving, Privacy-preserving techniques, review, Sensitive data, trustworthiness
@article{elhajjoutFederatedLargeLanguage2026,
title = {Federated Large Language Models for A Trustworthy and Privacy-Preserving Healthcare: Applications, Challenges, and Future Research Directions},
author = {A. Elhajjout and Z. A. E. Houda and H. Moudoud and B. Brik and M. A. Jan},
url = {https://www.scopus.com/pages/publications/105034640126?origin=resultslist},
doi = {10.1109/JBHI.2026.3679612},
issn = {21682194 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {IEEE Journal of Biomedical and Health Informatics},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Large-scale foundation models, especially Federated Large Language Models (FLLMs), aim to transform digital health by enabling clinically-grade natural language processing while keeping sensitive data local. However, their adoption is hindered by two main issues: (i) the computational and communication burden of parameter-rich models on resource-constrained Internet-of-Medical-Things (IoMT) devices, and (ii) performance degradation caused by Non-Independent and Identically Distributed (Non-IID) patient data. This paper presents a comprehensive survey of Federated Learning (FL) for LLMs in Healthcare (FedMed-LLMs). We review the foundations of FL and medical LLMs. Then, we present the FL-enabled LLMs applications in healthcare, and we examine their issues in terms of privacy, robustness, and trustworthiness. Finally, we present a set of core research problems and a comprehensive research agenda that identifies future directions for building robust and scalable FedMed-LLMs systems. © 2013 IEEE.},
keywords = {Application research, Artificial intelligence, digital health, Distributed computer systems, Federated learning, Fine tuning, Health care, Health care application, Healthcare AI, human, Internet, Internet of medical thing, Internet of Medical Things, Language model, Large language model, large language models, Learning systems, male, Medical computing, natural language processing, Parameter-efficient fine-tuning, patient coding, Privacy, Privacy preservation, Privacy preserving, Privacy-preserving techniques, review, Sensitive data, trustworthiness},
pubstate = {published},
tppubtype = {article}
}
Large-scale foundation models, especially Federated Large Language Models (FLLMs), aim to transform digital health by enabling clinically-grade natural language processing while keeping sensitive data local. However, their adoption is hindered by two main issues: (i) the computational and communication burden of parameter-rich models on resource-constrained Internet-of-Medical-Things (IoMT) devices, and (ii) performance degradation caused by Non-Independent and Identically Distributed (Non-IID) patient data. This paper presents a comprehensive survey of Federated Learning (FL) for LLMs in Healthcare (FedMed-LLMs). We review the foundations of FL and medical LLMs. Then, we present the FL-enabled LLMs applications in healthcare, and we examine their issues in terms of privacy, robustness, and trustworthiness. Finally, we present a set of core research problems and a comprehensive research agenda that identifies future directions for building robust and scalable FedMed-LLMs systems. © 2013 IEEE.
3.
Ledrou-Paquet, V.; Fiset, D.; Carré, M.; Guérette, J.; Blais, C.
The facial information underlying economic decision-making Article de journal
Dans: Perception, vol. 55, no 3, p. 243–265, 2026, ISSN: 03010066 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Adolescent, adult, Bubbles, decision making, face evaluation, face perception, Facial Expression, Facial Recognition, facial trustworthiness, female, human, Humans, Judgment, male, perception, physiology, psychology, Social Perception, Trust, trust game, trustworthiness, Young Adult
@article{ledrou-paquetFacialInformationUnderlying2026,
title = {The facial information underlying economic decision-making},
author = {V. Ledrou-Paquet and D. Fiset and M. Carré and J. Guérette and C. Blais},
url = {https://www.scopus.com/pages/publications/105020458633?origin=resultslist},
doi = {10.1177/03010066251387848},
issn = {03010066 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Perception},
volume = {55},
number = {3},
pages = {243–265},
publisher = {SAGE Publications Ltd},
abstract = {Faces are rapidly and automatically assessed on multiple social dimensions, including trustworthiness. The high inter-rater agreement on this social judgment suggests a systematic association between facial appearance and perceived trustworthiness. The facial information used by observers during explicit trustworthiness judgments has been studied before. However, it remains unknown whether the same perceptual strategies are used during decisions that involve trusting another individual, without necessitating an explicit trustworthiness judgment. To explore this, 53 participants completed the Trust Game, an economic decision task, while facial information was randomly sampled using the Bubbles method. Our results show that economic decisions based on facial cues rely on similar visual information as that used during explicit trustworthiness judgments. We then manipulated facial features identified as diagnostic for trust to test their influence on perceived trustworthiness (Experiment 2) and on trust-related behaviors (Experiment 3). Across all experiments, subtle, targeted changes to facial features systematically shifted both impressions and monetary trust decisions. These findings demonstrate that the same perceptual strategies underlie explicit judgments and trust behaviors, highlighting the applied relevance of even minimal alterations in facial appearance. These findings should be replicated with real faces from diverse demographic backgrounds to confirm their generalizability. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).},
keywords = {Adolescent, adult, Bubbles, decision making, face evaluation, face perception, Facial Expression, Facial Recognition, facial trustworthiness, female, human, Humans, Judgment, male, perception, physiology, psychology, Social Perception, Trust, trust game, trustworthiness, Young Adult},
pubstate = {published},
tppubtype = {article}
}
Faces are rapidly and automatically assessed on multiple social dimensions, including trustworthiness. The high inter-rater agreement on this social judgment suggests a systematic association between facial appearance and perceived trustworthiness. The facial information used by observers during explicit trustworthiness judgments has been studied before. However, it remains unknown whether the same perceptual strategies are used during decisions that involve trusting another individual, without necessitating an explicit trustworthiness judgment. To explore this, 53 participants completed the Trust Game, an economic decision task, while facial information was randomly sampled using the Bubbles method. Our results show that economic decisions based on facial cues rely on similar visual information as that used during explicit trustworthiness judgments. We then manipulated facial features identified as diagnostic for trust to test their influence on perceived trustworthiness (Experiment 2) and on trust-related behaviors (Experiment 3). Across all experiments, subtle, targeted changes to facial features systematically shifted both impressions and monetary trust decisions. These findings demonstrate that the same perceptual strategies underlie explicit judgments and trust behaviors, highlighting the applied relevance of even minimal alterations in facial appearance. These findings should be replicated with real faces from diverse demographic backgrounds to confirm their generalizability. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
4.
Ledrou-Paquet, V.; Fiset, D.; Carré, M.; Guérette, J.; Blais, C.
The facial information underlying economic decision-making Article de journal
Dans: Perception, vol. 55, no 3, p. 243–265, 2026, ISSN: 03010066 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Bubbles, face evaluation, face perception, facial trustworthiness, Social Perception, trust game, trustworthiness
@article{ledrou-paquetFacialInformationUnderlying2026a,
title = {The facial information underlying economic decision-making},
author = {V. Ledrou-Paquet and D. Fiset and M. Carré and J. Guérette and C. Blais},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105020458633&doi=10.1177%2F03010066251387848&partnerID=40&md5=7c1ead96fa13944073ed63bc952ca723},
doi = {10.1177/03010066251387848},
issn = {03010066 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Perception},
volume = {55},
number = {3},
pages = {243–265},
abstract = {Faces are rapidly and automatically assessed on multiple social dimensions, including trustworthiness. The high inter-rater agreement on this social judgment suggests a systematic association between facial appearance and perceived trustworthiness. The facial information used by observers during explicit trustworthiness judgments has been studied before. However, it remains unknown whether the same perceptual strategies are used during decisions that involve trusting another individual, without necessitating an explicit trustworthiness judgment. To explore this, 53 participants completed the Trust Game, an economic decision task, while facial information was randomly sampled using the Bubbles method. Our results show that economic decisions based on facial cues rely on similar visual information as that used during explicit trustworthiness judgments. We then manipulated facial features identified as diagnostic for trust to test their influence on perceived trustworthiness (Experiment 2) and on trust-related behaviors (Experiment 3). Across all experiments, subtle, targeted changes to facial features systematically shifted both impressions and monetary trust decisions. These findings demonstrate that the same perceptual strategies underlie explicit judgments and trust behaviors, highlighting the applied relevance of even minimal alterations in facial appearance. These findings should be replicated with real faces from diverse demographic backgrounds to confirm their generalizability. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).},
keywords = {Bubbles, face evaluation, face perception, facial trustworthiness, Social Perception, trust game, trustworthiness},
pubstate = {published},
tppubtype = {article}
}
Faces are rapidly and automatically assessed on multiple social dimensions, including trustworthiness. The high inter-rater agreement on this social judgment suggests a systematic association between facial appearance and perceived trustworthiness. The facial information used by observers during explicit trustworthiness judgments has been studied before. However, it remains unknown whether the same perceptual strategies are used during decisions that involve trusting another individual, without necessitating an explicit trustworthiness judgment. To explore this, 53 participants completed the Trust Game, an economic decision task, while facial information was randomly sampled using the Bubbles method. Our results show that economic decisions based on facial cues rely on similar visual information as that used during explicit trustworthiness judgments. We then manipulated facial features identified as diagnostic for trust to test their influence on perceived trustworthiness (Experiment 2) and on trust-related behaviors (Experiment 3). Across all experiments, subtle, targeted changes to facial features systematically shifted both impressions and monetary trust decisions. These findings demonstrate that the same perceptual strategies underlie explicit judgments and trust behaviors, highlighting the applied relevance of even minimal alterations in facial appearance. These findings should be replicated with real faces from diverse demographic backgrounds to confirm their generalizability. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).