標題: Titlebook: Explainable Artificial Intelligence; First World Conferen Luca Longo Conference proceedings 2023 The Editor(s) (if applicable) and The Auth [打印本頁] 作者: FORAY 時間: 2025-3-21 18:29
書目名稱Explainable Artificial Intelligence影響因子(影響力)
作者: squander 時間: 2025-3-21 23:50
Evaluating Self-attention Interpretability Through Human-Grounded Experimental Protocolntly better than a random baseline regarding average participant reaction time and accuracy. Moreover, data analysis highlights that high probability prediction induces great explanation relevance. This work shows how self-attention can be aggregated and used to explain Transformer classifiers. The 作者: 哪有黃油 時間: 2025-3-22 03:56 作者: 烤架 時間: 2025-3-22 07:51 作者: 遭遇 時間: 2025-3-22 11:53 作者: 危機 時間: 2025-3-22 16:17
Causal-Based Spatio-Temporal Graph Neural Networks for?Industrial Internet of?Things Multivariate Tidata features effectively. Experimental results on industrial datasets demonstrate that the proposed method outperforms existing baselines and achieves state-of-the-art performance. The proposed approach offers a promising solution for accurate and interpretable spatio-temporal data forecasting.作者: 危機 時間: 2025-3-22 20:57 作者: 描繪 時間: 2025-3-23 00:32 作者: syring 時間: 2025-3-23 03:36 作者: nutrition 時間: 2025-3-23 06:46
Development of?a?Human-Centred Psychometric Test for?the?Evaluation of?Explanations Produced by?XAI ability. The questionnaire development process was divided into two phases. First, a pilot study was designed and carried out to test the first version of the questionnaire. The results of this study were exploited to create a second, refined version of the questionnaire. The questionnaire was evalu作者: 內(nèi)部 時間: 2025-3-23 13:43
Adding Why to?What? Analyses of?an?Everyday Explanationfrom a video recall to explore how Explainers (EX) justified their explanation. We found that EX were focusing on the physical aspects of the game first (Architecture) and only later on aspects of the Relevance. Reasoning in the video recalls indicated that EX regarded the focus on the Architecture 作者: crease 時間: 2025-3-23 17:09 作者: objection 時間: 2025-3-23 18:29
The Importance of?Distrust in?AIto prevent both disuse of these systems as well as overtrust. From our analysis of research on interpersonal trust, trust in automation, and trust in (X)AI, we identify the potential merit of the distinction between trust and distrust (in AI). We propose that alongside trust a healthy amount of dist作者: ungainly 時間: 2025-3-23 23:08
Leveraging Group Contrastive Explanations for?Handling Fairnesssights through a comprehensive explanation of the decision-making process, enabling businesses to: detect the presence of direct discrimination on the target variable and choose the most appropriate fairness framework.作者: Generator 時間: 2025-3-24 02:51
Handbook of Phenomenological Aesthetics problem-solving strategies. Additionally, by inspecting the attention weights layer by layer, we uncover an unconventional finding that layer 10, rather than the model’s final layer, is the optimal layer to unfreeze for the least parameter-intensive approach to fine-tune the model. We support these作者: FUME 時間: 2025-3-24 09:31 作者: JOG 時間: 2025-3-24 14:09 作者: TAG 時間: 2025-3-24 18:52 作者: 微枝末節(jié) 時間: 2025-3-24 22:10 作者: 洞穴 時間: 2025-3-25 01:37
Handbook of Philosophical Logicdata features effectively. Experimental results on industrial datasets demonstrate that the proposed method outperforms existing baselines and achieves state-of-the-art performance. The proposed approach offers a promising solution for accurate and interpretable spatio-temporal data forecasting.作者: 云狀 時間: 2025-3-25 06:08
Handbook of Philosophical Logic features from the EEG data. Despite impressive test accuracy, a fundamental need remains for an in-depth comprehension of the models. Attributions proffer initial insights into the decision-making process. Still, they did not allow us to determine why specific channels are more contributory than ot作者: Narcissist 時間: 2025-3-25 10:03 作者: hallow 時間: 2025-3-25 14:40 作者: 推延 時間: 2025-3-25 18:30
Islamism and the Political Orderability. The questionnaire development process was divided into two phases. First, a pilot study was designed and carried out to test the first version of the questionnaire. The results of this study were exploited to create a second, refined version of the questionnaire. The questionnaire was evalu作者: homeostasis 時間: 2025-3-25 21:33 作者: Diuretic 時間: 2025-3-26 03:11 作者: 使更活躍 時間: 2025-3-26 06:11 作者: WAG 時間: 2025-3-26 11:07 作者: FRAUD 時間: 2025-3-26 16:36
Conference proceedings 2023series and Natural Language Processing;?Human-centered explanations and xAI for Trustworthy and Responsible AI;?Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI..作者: 明智的人 時間: 2025-3-26 17:03
1865-0929 for time series and Natural Language Processing;?Human-centered explanations and xAI for Trustworthy and Responsible AI;?Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI..978-3-031-44069-4978-3-031-44070-0Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: DEMN 時間: 2025-3-26 21:55 作者: 潰爛 時間: 2025-3-27 02:38 作者: Insufficient 時間: 2025-3-27 06:25
Power, Politics, and the Civil Sphereingful concepts achieving 4.8% higher concept completeness and 36.5% lower purity scores on average, (iii) provide high-quality concept-based logic explanations for their prediction, and (iv) support effective interventions at test time: these can increase human trust as well as improve model performance.作者: cancellous-bone 時間: 2025-3-27 10:17 作者: Hormones 時間: 2025-3-27 15:20 作者: TSH582 時間: 2025-3-27 19:48
Hassan Namazi,Mohsen Mosadegh,Mozhgan Hayasi or not. In this paper, we study an out-of-distribution (OoD) detection approach based on a rule-based eXplainable Artificial Intelligence (XAI) model. Specifically, the method relies on an innovative metric, i.e., the weighted mutual information, able to capture the different way decision rules are used in case of in- and OoD data.作者: ECG769 時間: 2025-3-27 22:23 作者: 賠償 時間: 2025-3-28 03:12
Weighted Mutual Information for?Out-Of-Distribution Detection or not. In this paper, we study an out-of-distribution (OoD) detection approach based on a rule-based eXplainable Artificial Intelligence (XAI) model. Specifically, the method relies on an innovative metric, i.e., the weighted mutual information, able to capture the different way decision rules are used in case of in- and OoD data.作者: 停止償付 時間: 2025-3-28 09:28
Communications in Computer and Information Sciencehttp://image.papertrans.cn/e/image/319287.jpg作者: 享樂主義者 時間: 2025-3-28 14:22 作者: TOXIC 時間: 2025-3-28 16:23
Body and Movement: Basic Dynamic Principles,er, Transformers remain hard to interpret and are considered as black-boxes. In this paper we assess how attention coefficients from Transformers help in providing classifier interpretability when properly aggregated. A fast and easy-to-implement way of aggregating attention is proposed to build loc作者: 流動性 時間: 2025-3-28 20:19
Handbook of Philosophical Logico find and remove online hate speech, which would address a critical problem. A variety of explainable AI strategies are being developed to make model judgments and justifications intelligible to people as artificial intelligence continues to permeate numerous industries and make critical change. Ou作者: 我正派 時間: 2025-3-29 01:39
Handbook of Philosophical Logic, in order to explain them to humans. Social science research states that such explanations should be conversational, similar to human-to-human explanations. In this work, we show how to incorporate XAI in a conversational agent, using a standard design for the agent comprising natural language unde作者: phase-2-enzyme 時間: 2025-3-29 06:21 作者: incisive 時間: 2025-3-29 11:07 作者: THE 時間: 2025-3-29 13:20
Handbook of Philosophical Logicnd authentication methods. This research comprehensively compared EEG data pre-processing techniques, focusing on biometric applications. In tandem with this, the study illuminates the pivotal role of Explainable Artificial Intelligence (XAI) in enhancing the transparency and interpretability of mac作者: 香料 時間: 2025-3-29 15:50
Handbook of Philosophical Logic are based on implicit time series information, ranging from contextual recommendations on smartwatches to human activity recognition on production workshop. Despite the advantages of these systems, the opaqueness and unpredictability of these systems for users has elicited concerns. To mitigate the作者: 珊瑚 時間: 2025-3-29 21:31
Handbook of Plant Ecophysiology Techniquesrning models has increased. In particular, XAI for time series data has become increasingly important in finance, healthcare, and climate science. However, evaluating the quality of explanations, such as attributions provided by XAI techniques, remains challenging. This paper provides an in-depth an作者: esculent 時間: 2025-3-30 02:26 作者: 星球的光亮度 時間: 2025-3-30 07:25
Islamism and the Political Ordere it comprehensible for humans. To reach it, it is necessary to have a reliable tool to collect the opinions of human users about the explanations generated by XAI methods of trained complex models. Psychometrics can be defined as the science behind psychological assessment. It studies the theory an作者: 別名 時間: 2025-3-30 08:50
Power, Politics, and the Civil Sphereing post-hoc explanations, however, they fail to make the model itself more interpretable. To fill this gap, we introduce the Concept Distillation Module, the first differentiable concept-distillation approach for graph networks. The proposed approach is a layer that can be plugged into any graph ne作者: 寬大 時間: 2025-3-30 15:04 作者: STRIA 時間: 2025-3-30 16:52 作者: intoxicate 時間: 2025-3-30 22:15 作者: hidebound 時間: 2025-3-31 02:23
Hassan Namazi,Mohsen Mosadegh,Mozhgan Hayasiot (in- or out-of-distribution) to the ones the ML system has been trained on may lead to potentially fatal consequences. Operational data compliance with the training data has to be verified by the data analyst, who must also understand, in operation, if the autonomous decision-making is still safe作者: GREEN 時間: 2025-3-31 05:48
Popular Narratives of the Cochlear Implantnot discriminate against specific groups of people becomes crucial. Reaching this objective requires a multidisciplinary approach that includes domain experts, data scientists, philosophers, and legal experts, to ensure complete accountability for algorithmic decisions. In such a context, Explainabl作者: 溺愛 時間: 2025-3-31 11:50
978-3-031-44069-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 砍伐 時間: 2025-3-31 14:06
Explainable Artificial Intelligence978-3-031-44070-0Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: LIMN 時間: 2025-3-31 20:54
https://doi.org/10.1007/978-3-031-44070-0artificial intelligence; interpretable machine learning; causal inference & explanations; argumentative作者: Enervate 時間: 2025-4-1 00:03
Opening the?Black Box: Analyzing Attention Weights and?Hidden States in?Pre-trained Language Models e recent advancements in pre-trained language models based on transformers and their increasing integration into daily life, addressing this issue has become more pressing. In order to achieve an explainable AI model, it is essential to comprehend the procedural steps involved and compare them with
