Zobrazeno 1 - 10
of 11 609
pro vyhledávání: '"Fukuchi A"'
Autor:
Fukuchi, Yosuke, Yamada, Seiji
This paper reviews our previous trials of Nudge-XAI, an approach that introduces automatic biases into explanations from explainable AIs (XAIs) with the aim of leading users to better decisions, and it discusses the benefits and challenges. Nudge-XAI
Externí odkaz:
http://arxiv.org/abs/2406.07323
This study considers the attack on reinforcement learning agents where the adversary aims to control the victim's behavior as specified by the adversary by adding adversarial modifications to the victim's state observation. While some attack methods
Externí odkaz:
http://arxiv.org/abs/2406.03862
Transfer learning enhances prediction accuracy on a target distribution by leveraging data from a source distribution, demonstrating significant benefits in various applications. This paper introduces a novel dissimilarity measure that utilizes vicin
Externí odkaz:
http://arxiv.org/abs/2405.16906
Deep learning models are susceptible to adversarial attacks, where slight perturbations to input data lead to misclassification. Adversarial attacks become increasingly effective with access to information about the targeted classifier. In the contex
Externí odkaz:
http://arxiv.org/abs/2405.15244
Prior work on multilingual sentence embedding has demonstrated that the efficient use of natural language inference (NLI) data to build high-performance models can outperform conventional methods. However, the potential benefits from the recent ``exp
Externí odkaz:
http://arxiv.org/abs/2403.17528
Autor:
Fukuchi, Yosuke, Yamada, Seiji
Communication robots have the potential to contribute to effective human-XAI interaction as an interface that goes beyond textual or graphical explanations. One of their strengths is that they can use physical and vocal expressions to add detailed nu
Externí odkaz:
http://arxiv.org/abs/2403.14550
Autor:
Fukuchi, Yosuke, Yamada, Seiji
This paper addresses the challenge of selecting explanations for XAI (Explainable AI)-based Intelligent Decision Support Systems (IDSSs). IDSSs have shown promise in improving user decisions through XAI-generated explanations along with AI prediction
Externí odkaz:
http://arxiv.org/abs/2402.18016
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-6 (2024)
Abstract Quantitative biomechanical gait analysis is an important clinical and research tool for injury and disease diagnosis and treatment. However, one major criticism is that gait analysis laboratories largely operate in isolation and there is a l
Externí odkaz:
https://doaj.org/article/a6913051bdf6477a84a8a13c8bfcb3ec
Publikováno v:
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023
A concept-based classifier can explain the decision process of a deep learning model by human-understandable concepts in image classification problems. However, sometimes concept-based explanations may cause false positives, which misregards unrelate
Externí odkaz:
http://arxiv.org/abs/2305.18362
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Motor contagions refer to implicit effects induced by the observation of actions made by others on one’s own actions. A plethora of studies conducted over the last two decades have demonstrated that both observed and predicted actions can
Externí odkaz:
https://doaj.org/article/586800da3a0c429e89491b0b89ecdf36