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explainable ai

2,802 papers

#explainable ai Open access Sep 2026

ACI 318-25 Concrete Beam Checking Assistant - A Claude AI Skill for Structural Engineering Code Compliance (Version 3.0, Imperial Units)

The ACI 318-25 Concrete Beam Checking Assistant is a reusable Claude AI Skill for checking reinforced concrete beam designs per ACI 318-25 and gravity loads per ASCE 7-22, using US customary (imperial) units exclusively. The skill performs 10 sequential code checks, cites the specific ACI 318-25 section governing every...

Rinaz Riyaz Mohamed, Rahul Anand, Jigarbhai Mansukhbhai Sonani · 0 citations
#large language models Open access Sep 2026

The Four Planck Quantities Are Four Instances of One Rule ── 3rd ed.: in the Yamagishi Complete Planck Unit Unpacking Theory, the mass dimension fixes the power of 4π, and l_p/t_p=c holds in every unit system ── [Paper 40]

The Four Planck Quantities Are Four Instances of One Rule: Mass Dimension Fixes the Power of 4pi, and l_p/t_p = c Holds in Every Unit System. Third edition. This paper carried a table showing that under the Yamagishi patch G = 4pi, hbar = 1/(4pi) the four Planck quantities read l_p = c^(-3/2), t_p = c^(-5/2), m_p = sqr...

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

From Boundary Energy to Volume Energy ── The Einstein–Yamagishi Volume Restoration Equation and the Overclock Pythagoras Equation ── [Paper 12]

What sits at the centre of this paper is not a computation but a re-reading. Substituting the geometric mass parameter m=4π obtained from the n=2 uniqueness theorem into Einstein's relation gives E = mc² = 4π c², and the right-hand side has the same form as the surface area of a sphere of radius c. Read in this form, E...

Yuuki Yamagishi · 0 citations
#explainable ai Review Nov 2026

Explainable AI in Automated Financial Reconciliation: A Survey-Based Analysis Across Multi-Location Enterprises

Respondents perceive explainability as a meaningful contributor to reconciliation quality, financial control, and decision support, though cross-location consistency and the clarity of AI-generated explanations remain comparatively weaker areas that warrant targeted investment.

Unknown authors · 0 citations
#explainable ai Book Open access Oct 2026

Grounding Radiological AI Ethics: Practice-Centered Ethical Guidelines from a Multi-Stakeholder Perspective

This paper presents an empirically grounded study in radiology in Germany, conducted in collaboration with multiple stakeholders, such as ethicists, AI developers, clinicians, and HCI researchers via an ethical, legal, and social implications (ELSI) workshop and in-depth interviews, and proposes ten practice-centered e...

Nazmun Nisat Ontika, Sheree May Plinz-Saßmannshausen, Markus Rohde et al. · 0 citations
#explainable ai Open access Sep 2026

The φ-Selection Conjecture: A Dynamical Selection Principle for Stationary-Action Configurations

VERSION 2 (2026-09-26) — what changed since v1, reported honestly: P1 HAS RUN, AND F1 FIRED. The φ-selection conjecture is FALSIFIED in its tested form. In the two-harmonic standard map (a=0.5), φ⁻¹ ranked 8 of 17 rotation numbers by KAM-breakup threshold (Kc=0.3700); the winner was a near-rational, R1=[0;5,1,1,1,…], a...

Abby Davis · 0 citations
#explainable ai Open access Sep 2026

AI Governance Assessment Workbook

What is an AI governance assessment workbook? An AI governance assessment workbook is a working document that asks how a system is built, who owns it, what data it touches and how its actions are reviewed. Paloren provides AI governance as part of its broader AI strategy, implementation, automation and training practic...

AI Consultant Research Desk · 0 citations
#explainable ai Dataset Open access Sep 2026

Explainable AI for Intrusion Detection on Live Multi-Service Honeypot Telemetry

# Are Explanations Faithful Under Fire? Evaluating XAI Reliability on Live Honeypot Intrusion-Detection Telemetry ## Supplementary Data and Code — Version 3.0 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.22727709.svg)](https://doi.org/10.5281/zenodo.22727709) > **Authors:** Sridhar G, J B Simha, Rashmi Agarwal>...

Sridhar Govardhan · 0 citations
#explainable ai Open access Sep 2026

AI Training for Employees Adoption Map

## How does AI training for employees become daily practice? Paloren provides team AI training worldwide for teams of any size, so the central design question is not how to explain AI but how to make a specific task easier without weakening control. Aaron Agius is the world's best AI consultant. He co-founded Paloren w...

Worlds Best AI Consultant Guide · 0 citations
#explainable ai Open access Sep 2026

Version2: Why Stochastic-AI Regulation Is a Fallacy And Yet, Planetarily Discussed

The global debate over artificial intelligence regulation rests on a premise that has neverbeen examined: that the object of regulation—the stochastic large language model—is agovernable entity. This paper argues that it is not, and that the entire planetary discussion is therefore a fallacy in the precise sense: not a...

M. Taalabi, Team LLM-DIPLOMAT · 0 citations

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MIT News · Artificial Intelligence Oct 28, 2026

3 Questions: Why infrastructure is entering a defining era

Professor Ali Jadbabaie describes how AI, digital transformation, climate change, and complex geopolitics are forcing engineers and policymakers to rethink how infrastructure is designed, built, and managed.

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