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explainable ai

2,387 papers

#large language models Open access Sep 2026

Same Atomic Number, Same Charge, Same Electrons: Change Only the Mass and the Rate Moves Sevenfold ── The C--H to C--D frequency ratio is 0.734230, which is not 1/sqrt(2)=0.707107 ── A zero-point difference of 4.7690 kJ/mol makes k_H/k_D=6.8468 at room temperature ── [Paper 341]

Replace hydrogen with deuterium and a reaction rate changes. This paper asks why changing only the mass moves the rate──the answer is that the energy of standing still is set by the mass. No new mathematical theorem and no new law is claimed. Scope of this paper (scope note): No new mathematical theorem and no new law...

Yuuki Yamagishi · 0 citations
#large language models Open access Sep 2026

Ethical tensions in AI-mediated clinical communication: a mixed-methods study of nursing students’ perspectives

The increasing use of artificial intelligence (AI), particularly large language models (LLMs), is reshaping clinical communication by influencing how patients access, interpret, and act upon clinical information. Recent conceptual work has suggested that AI-mediated communication raises ethical questions concerning int...

Xiongwen Yang, Yi Xiao, Di Liu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Improving 5G AI-RAN MCS Selection by Predicting Retransmissions

Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the channel changes quickly. This data is also noisy, making it hard to track accurately, and has to be fed to real-time controllers with feedback-loop effects which are hard to...

Tamerlan Aghayev, Maxime Elkael, Michele Polese et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Seven Sources of Physical AI Capability Formation

The framework distinguishes similarity in observed capability from similarity in how it was formed, supporting analysis of explanation, transfer, replication, dependencies, governance evidence, and geoeconomic foundations.

Gang Chen · 0 citations
#artificial intelligence Preprint Sep 2026

XAI-Arena: Can LLMs Assess the Quality of XAI Explanations?

Evaluating the quality of explanations produced by explainable AI (XAI) methods remains challenging because existing approaches often rely on subjective human judgment, limiting reproducibility, scalability, and comparability between studies. We examine whether LLMs can serve as a reproducible and scalable mechanism to...

Yanfei Hu Fleischhauer, Alona Zharova, Nadja Klein et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Adaptive Entangled Game Modules in Artificial General Intelligence

We introduce a probability-wave framework for modeling the collective behavior of interacting adaptive agents, deriving testable eigenmodes through a generalized behavioral intelligence (GBI) nonlocal probability-wave equation. This framework captures a broad range of human intelligence behaviors with analytical mechan...

Hao-Chen Li, Xin-Shuai Guo, Jing Ouyang et al. · 0 citations
#explainable ai Review Sep 2026

A Data‐to‐Interface Framework for AI‐Guided Sodium‐Ion Battery Materials Discovery: From Descriptors to Full‐Cell Decisions

A sodium‐specific minimum reporting profile for uncertainty‐aware, descriptor‐driven, and interface‐validated decision‐making is proposed for sodium‐specific minimum reporting profile for uncertainty‐aware, descriptor‐driven, and interface‐validated decision‐making.

Gang Chen, Hong-Yang Zhao, Jun-Feng Li et al. · 0 citations
#explainable ai Open access Sep 2026

Integrating Artificial Intelligence and Data Science for Financial Decision-making and Business Performance Optimization

Overall, the findings indicate that business value is associated not simply with AI adoption, but with its systematic integration into financial decision-making processes.

Patricia Ugochi Uzoma, Kehinde Akinwale, Blessing Itodo et al. · 0 citations
#explainable ai Open access Sep 2026

Posterior Tracheal Wall Dysfunction in Excessive Dynamic Airway Collapse: Reviewing the Role of the Posterior Membranous Wall

Poster presentation at the 9th International Conference on Molecular Biology and Biotechnology (ICMBB) 2026, “Transdisciplinary Innovation: Advancing Science through Responsible Use of AI for Human and Planetary Well-being”July 14–16, 2026, UCSI University in Kuala Lumpur, Malaysia. The presentation, titled "Posterior...

Nor Amizan Mohd Sabri, Masaany Mansor, Norazila Abdul Rahim et al. · 0 citations
#generative ai Open access Sep 2026

Deepfake Abuse and Gendered Digital Creative Violence: Feminist AI Interventions from Mexico

It is argued that creative violence offers a transferable framework for understanding emerging forms of generative harm beyond deepfakes by shifting attention from reactive content moderation to the politics of creation itself.

Payal Arora, Ana María Miranda Mora, M. Zarzycka · 0 citations
#explainable ai Open access Sep 2026

THE BRIDGE CHOMSKY NEVER BUILT: Innate Language, Innate Freedom, and a Candidate Ground

Abstract Chomsky built two great things and never joined them. In linguistics, he argued that humans are born with a language faculty — and he won that argument by refusing to accept a named capacity as an explanation. In politics, he argued that authority must justify itself because humans have an instinct for freedom...

José Caetano de Mattos · 0 citations
#explainable ai Open access Sep 2026

Deepfake as algorithmic political culture: Negotiating communicative trust, authenticity, power, and public meaning during Indonesia's 2025 demonstrations

The rapid advancement of generative artificial intelligence has transformed the landscape of political communication by challenging the authenticity and credibility of visual evidence during public protests. Indonesia's 2025 national demonstrations provide a strategic empirical context for examining this transformation...

Julia Magdalena Wuysang, Ira Patriani, Asmadi 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.

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