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generative ai

2,538 papers

#generative ai Open access Oct 2026

Expression, Verification, and the Scarcity of Aesthetic Education: Reinterpreting Moral Rights in the Age of Generative AI

This paper argues that the denial of copyright and moral rights to works substantially shaped by human expressive judgment in generative AI systems produces two interrelated harms: the incentive to conceal AI involvement (“trace forgery”) and the proliferation of low-quality content (“flooding”). Drawing on R. G. Colli...

Carter · 0 citations
#generative ai Oct 2026

Introduction to Generative AI for CAV Systems

This chapter introduces the fundamental distinction between generative and discriminative AI, establishing the conceptual foundation for understanding how generative models enable transformative capabilities in connected and autonomous vehicles (CAVs). Unlike traditional discriminative systems that classify inputs into...

Kyungtae Han · 0 citations
#generative ai Open access Oct 2026

Generative AI as a Catalyst: Transforming Digital Literacy Practices in English Language Teaching

The increasing integration of Generative Artificial Intelligence (GenAI) in English language teaching calls for an immediate and thorough response from language teachers. Employing an exploratory qualitative approach, the study explores how 10 English language instructors at a Chinese university integrate GenAI tools i...

Yuwei Wan, Benjamin Luke Moorhouse · 0 citations
#generative ai Open access Oct 2026

Evaluating the constructiveness and professional tone of AI-generated corrective feedback for medical learners

Faculty feedback is vital for the professional growth of learners. Barriers such as faculty’s confidence in their feedback skills and time limitations may inhibit the provision of quality feedback. Generative large language models (LLMs), such as ChatGPT, have the potential to support faculty in providing high-quality...

Bonnie Desselle, Emma Simon, Amy Prudhomme et al. · 0 citations
#generative ai Open access Oct 2026

Using AI, Doubting AI: Developer Mental Models and Trust in AI-Assisted Software Work

Generative AI has entered software work with remarkable speed, yet trust in its output remains unsettled. This study examines how developers and learners navigate AI-assisted software work through mental models and trust. Analyzing 40,052 responses from the 2025 Stack Overflow Developer Survey, the findings reveal a du...

NICOLE DSILVA · 0 citations
#generative ai Open access Oct 2026

Advancing Brain Tumor Management Using Generative AI: A Comprehensive Review of MRI-Based Applications

Purpose: To systematically review the integration of generative artificial intelligence (GenAI) in MRI-based brain tumor management and evaluate its impact on detection, segmentation, diagnosis, treatment planning, and outcome prediction. The review addresses the research question like How effectively can GenAI enhance...

Ankita Shukla, Smitha Jha, Amrita Sarkar · 0 citations
#generative ai Book Oct 2026

Teaching English as a Second Language in an Evolving Digital Landscape

Intensive English Programs have undergone major changes in how technology supports language education and research. At the University of Pittsburgh&s;s English Language Institute, early efforts centered on custom-built software that supported both classroom instruction and research, culminating in projects such as the...

B.C.R. Price · 0 citations
#generative ai Open access Oct 2026

TITLE Conceptual Worldbuilding & Generative Realities at the Limit DESCRIPTION Conceptual Worldbuilding & Generative Realities at the Limit develops a falsifiable research architecture for turning concepts into interactive digital worlds, social simulations, digital twins, and institutional prototypes without confusing internal coherence with external reality. The book is organized around a core tri-coupling: Conceptual Rules × Executable Worlds × Reality Feedback. Its central candidate relation is WorldValidity = RuleCoherence × TaskReplay × ExternalTransfer, with a strict condition: ExternalTransfer remains UNKNOWN until independently tested. Immersion, elegance, agent fluency, and repeated success inside a simulator are treated as insufficient evidence of causal validity in the physical or institutional world. The volume contains a thirty-formula mathematical prelude, eighty-two chapters in a single-section-per-page architecture, two hundred Research Gates, thirty-three Phoenix Answer Embryos, and 233 Easter-Egg Equations. It integrates state-space models, conservation laws, stochastic processes, causal inference, robust control, information theory, game theory, network dynamics, transfer geometry, digital-twin validation, rights constraints, resource ledgers, participatory governance, data portability, shutdown, and responsible world retirement. Five research layers structure the work: declaring boundaries and state transitions; compiling concepts into versioned rules; testing counterfactuals, scarcity, rights, and extreme conditions; cross-validating simulations with real-world data; and designing world branching, refusal, exit, shutdown, and succession. The result is a world-rule package, a digital-prototype methodology, and a transfer-failure map for researchers, designers, policymakers, AI system builders, and future civilizational studies. This is a research architecture rather than a claim that generated worlds are newly created physical universes. Book-defined equations are candidate models and indicators, not validated natural laws. Every major claim is paired with an applicability domain, measurement path, competing explanation, falsification boundary, and successor revision route. Author: Feng Cheng-En (pen name: 33)

TITLEConceptual Worldbuilding & Generative Realities at the Limit DESCRIPTIONConceptual Worldbuilding & Generative Realities at the Limit develops a falsifiable research architecture for turning concepts into interactive digital worlds, social simulations, digital twins, and institutional prototypes without confusing i...

33 · 0 citations
#generative ai Open access Oct 2026

OpenGEO: an open, reproducible, causal benchmark for Generative Engine Optimization

OpenGEO measures whether changing a piece of content changes whether an AI answer engine cites it. Documents are supplied to the model in context, so retrieval is held constant and the synthesis stage is measured in isolation. Every round uses a paired design in which only the document under test differs between arms,...

Lu Yang · 0 citations
#generative ai Book Oct 2026

All Travel Routes Radiate from AI

Red-and-gold galloping horses for the 2026 Spring Festival kickstarted a disruptive new era of Generative, Agentic and Embodied AI integrations. This chapter discusses how seemingly mundane interactions with technology are now loaded with AI meaning in China. After a quarter of a century of building industrial technolo...

Gary Bowerman · 0 citations
#generative ai Oct 2026

Using AI, Doubting AI: Developer Mental Models and Trust in AI-Assisted Software Work

Generative AI has entered software work with remarkable speed, yet trust in its output remains unsettled. This study examines how developers and learners navigate AI-assisted software work through mental models and trust. Analyzing 40,052 responses from the 2025 Stack Overflow Developer Survey, the findings reveal a du...

NICOLE DSILVA · 0 citations

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MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

GPT-Lab Oct 14, 2026

Building trustworthy AI: The role of AI harnesses, intent contracts and evals

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 Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.

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