Results 221 to 230 of about 96,849 (322)
British Journal of Social Psychology, Volume 65, Issue 3, July 2026.Abstract Intergroup contact is one of the most established approaches for improving relations between adversary groups in conflict settings; yet little is known about whether its effects might be shaped by the social context. In this paper, we examine whether pre‐war contact opportunity with the adversary group shapes the relationship between post‐war ...
Zaur Afandiyev +3 more
wiley +1 more source
Building centaur responders: is emergency management ready for artificial intelligence?
Disasters, Volume 50, Issue 3, July 2026.Abstract This article examines the preparedness of emergency management (EM) for addressing questions pertaining to artificial intelligence (AI), encompassing its benefits to EM missions, the potential biases, the societal impacts, and more. We pinpoint two key shortcomings in early EM research on AI: (i) insufficient discussion of both AI's history ...
Christopher Whyte +1 more
wiley +1 more source
AI Magazine, Volume 47, Issue 2, Summer 2026.Abstract AI systems are rapidly transitioning from laboratory demonstrations to decision‐making technologies deployed in high‐stakes domains. Yet reliability remains a primary obstacle to responsible adoption: discriminative models can be confidently wrong under out‐of‐distribution (OOD) inputs, and foundation models (FMs) such as large language models
Sean Du
wiley +1 more source
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
Applied AI Letters, Volume 7, Issue 2, June 2026.In this work, we have performed human‐based evaluation of three post hoc explainability techniques, Local Interpretable Model Agnostic Explanations (LIME), Shapely Additive Explanations (SHAP), and integrated Gradients (IG) for a multilingual Bidirectional Encoder Representations from Transformers (mBERT) based binary and multi‐label misogyny ...
Sargam Yadav +2 more
wiley +1 more source
Cross‐Method Explanation Stability Under Prediction‐Preserving Perturbations in Explainable AI
Applied AI Letters, Volume 7, Issue 2, June 2026.The cross‐method analysis showed common vulnerability patterns across gradient‐based and perturbation‐based explainers, whereas Grad‐CAM demonstrated a specific ability to be resilient. Further discussion revealed that, before prediction changes with increasing ε, explanation divergence could already have commenced, indicating that further explanation ...
Muhammad Hasnain +4 more
wiley +1 more source
eFood, Volume 7, Issue 3, June 2026.This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar +9 more
wiley +1 more source
eFood, Volume 7, Issue 3, June 2026.AI application can be very helpful in addressing different issues and shaping novel techniques in food production, food safety and quality, and food intake. AI application in food science, such as the food industry and processing, food safety and packaging, and nutrition.
Yaseen Galali +7 more
wiley +1 more source
Improving Implied Volatility Forecasts for American Options Using Neural Networks
Journal of Futures Markets, Volume 46, Issue 6, Page 1137-1153, June 2026.ABSTRACT This paper explores the application of neural networks to improve pricing of American options. Focusing on both American and European options on the S&P 100 index from January 2016 to August 2023, we integrate neural networks to model the difference between market‐implied and model‐implied volatilities derived from the Black‐Scholes and Heston
Haitong Jiang, Emese Lazar, Miriam Marra
wiley +1 more source
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep\n Classifiers [PDF]
, 2019 Ameya Joshi +3 more
openalex +1 more source