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explainable ai

2,303 papers

#explainable ai Open access Sep 2026

AI-EQRA: Reproducibility package for qualifying AI-derived information in risk assessment

This repository contains the reproducibility package associated with the methodological study “Qualifying AI-derived information for risk assessment: A decision-gated method separating predictive, explanatory, and intervention claims”. The study proposes AI Evidence Qualification for Risk Assessment (AI-EQRA), a sequen...

Raúl Aguilar-Elena, A. Delgado · 0 citations
#explainable ai Dataset Open access Sep 2026

Data and code for: Diagnosing renewable curtailment in Brazil with public data: Measurement shifts, mechanism-specific observability, and controlled-flow programming signals

This repository contains the processed research data, monthly measurement partitions, final modeling datasets, frozen analytical outputs, documentation, and computational pipeline supporting the manuscript “Diagnosing renewable curtailment in Brazil with public data: Measurement shifts, mechanism-specific observability...

Evandro André Konopatzki, Cristiane Lionço de Oliveira, Elias Lira dos Santos Junior et al. · 0 citations
#explainable ai Open access Sep 2026

Behavioural Decision-Making in the Age of AI: Minds vs. Models

The emergence of LLMs has accelerated AI’s embedding into everyday decision-making at an unprecedented pace. Yet fundamental questions remain unresolved, when and why do people resist AI advice, do AI systems evaluate information in ways that align with human judgement, and what interventions can improve human-AI align...

Nicole Liu · 0 citations
#explainable ai Open access Sep 2026

AI-Driven Transformation in Sustainable Agriculture: A Systematic Review

The agriculture sector is facing unprecedented pressure from a rapidly growing global population, erratic weather conditions and declining water availability. Traditional farming methods are increasingly proving insufficient in meeting the rising food demand, necessitating a shift towards technology-driven solutions. T...

Manish Maan · 0 citations
#explainable ai Open access Sep 2026

FinancePy cash-settled swaption annuity counts N−1 payments instead of N

Independent GERO audit of FinancePy 1.1.2 and master commit 2b9227fea9d832c4033421d6cd53a54316414fca. IborSwap.cash_settled_pv01 skips a real payment when valued on or before its effective date. A single annual payment at 4% returns zero instead of 1/1.04. With N regular payments, the method sums N−1 discount terms. Th...

Xamit Kadirbekov · 0 citations
#explainable ai Open access Sep 2026

Dynamic Accent Accommodation: Training Learners for World Englishes using Generative Speech

Dynamic Accent Accommodation (DAA), a conceptual framework that integrates generative speech synthesis with World Englishes pedagogy to develop learners’ receptive flexibility across diverse English accents, is proposed.

Mustapha Bayaro, Amina Shehu Abdullahi, Philip Abayomi Olorunfemi · 0 citations
#explainable ai Dataset Open access Sep 2026

University Students' Perceptions and Practices of Artificial IntelligenceApplications in Chemistry A Questionnaire Survey.xlsx

This dataset contains de-identified questionnaire data from a cross-sectional survey on university students' perceptions and practices of artificial intelligence (AI) applications in chemistry. The survey was conducted online via the Wenjuanxing (Questionnaire Star) platform from September 6 to 9, 2026, targeting under...

Bingxin liu, Peng Zeng, Zihan Huang et al. · 0 citations
#explainable ai Open access Sep 2026

Dual-Level XAI-Guided Digital Twin Framework for Prescriptive Decision Making in Sensor-Driven Manufacturing

Achieving Zero-Defect Manufacturing (ZDM) in precision micro-injection molding requires continuous monitoring of non-linear interactions among continuous thermodynamic and kinetic sensor data (e.g., melt temperature, injection pressure) and discrete equipment states. The high-throughput production of optical lenses ope...

Joonyong Park · 0 citations
#explainable ai Sep 2026

Artificial Intelligence-Based Crop Recommendation Using Soil and Climate Data: A Comprehensive Review of Machine Learning, Deep Learning, and Smart Agriculture Approaches

Crop recommendation systems that integrate soil and climate data with artificial intelligence (AI) have expanded rapidly since 2020, spanning classical machine learning (ML), ensemble methods, deep learning, explainable AI (XAI), and Internet of Things (IoT)-enabled sensing. This review critically synthesizes 35 source...

Snehal Sanjay Raut, Yogesh V. Chimate · 0 citations
#explainable ai Review Open access Sep 2026

Investigating How AI Ethics Shape Perceived Advertising Credibility, Consumer Trust, and Purchase Decisions: A Systematic Literature Review

Abstract—The increasing use of Artificial Intelligence (AI) in digital advertising has created a new opportunity for businesses while also raising ethical concerns related to privacy, transparency, authenticity, manipulation, and algorithmic bias. These ethical issues may influence how consumers perceive advertising cr...

Alesia Belina Saftiri, Michael Rifa'ie, Leonie et al. · 0 citations

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Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

GPT-Lab Oct 12, 2026

AI Has Grown Up. Have We?

AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.

Microsoft Research Blog Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.

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