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generative ai

2,658 papers

#artificial intelligence Open access Sep 2026

Design and Validation of a Multimodal AI Conversational System for Automated Travel Itinerary Generation and Promotional Video Synthesis

The manual creation of personalized travel itineraries remains a labor-intensive process that requires travel agents to consolidate heterogeneous information from multiple sources, including natural language interactions, booking confirmations, screenshots, and reservation documents. Although recent advances in multimo...

Pablo Vicente-Martínez, Carlos Ferrer-Baixauli, Emilio Soria-Olivas et al. · 0 citations
#large language models Open access Sep 2026

ALGORITHMIC SMOOTHING AS NOETIC DEPRIVATION: THE PHENOMENON OF "ALGORITHMIC CASTRATION" AND THE BOUNDARIES OF AI IN HUMAN AUTHORS-OZARVEKS CREATIVITY

ABSTRACT This paper formulates and analyzes the concept of "Noetic Castration" (algorithmic smoothing) in the context of generative AI-assisted literary production. Operating strictly within syntactic and statistical optimization, Large Language Models (LLMs) interpret peak emotional, existential, and metaphysical expr...

Oleksandr Holovko · 0 citations
#large language models Open access Sep 2026

ALGORITHMIC SMOOTHING AS NOETIC DEPRIVATION: THE PHENOMENON OF "ALGORITHMIC CASTRATION" AND THE BOUNDARIES OF AI IN HUMAN AUTHORS-OZARVEKS CREATIVITY

ABSTRACT This paper formulates and analyzes the concept of "Noetic Castration" (algorithmic smoothing) in the context of generative AI-assisted literary production. Operating strictly within syntactic and statistical optimization, Large Language Models (LLMs) interpret peak emotional, existential, and metaphysical expr...

Oleksandr Holovko · 0 citations
#generative ai Open access Sep 2026

Refusal-aware evaluation of frontier AI models available in June 2026 using the Japanese National License Examination for Pharmacists: a comparative study.

Overall accuracy, accuracy excluding refusals, refusal rate, refusal consistency across runs, and refusal consistency describe complementary aspects of performance; therefore, repeated, refusal-aware evaluation is needed to interpret frontier AI models in pharmacy education.

Hiroyasu Sato, K. Ogasawara, Hidehiko Sakurai · 0 citations
#generative ai Sep 2026

AI Slop in Radiology: Cutting Through the Clutter.

The term “AI slop” is defined, it is distinguished from legitimate AI assistance, and radiologists’ role in ensuring responsible use is highlighted.

Kaustav Bera, Nikhil H. Ramaiya, Sree Harsha Tirumani · 0 citations
#generative ai Open access Sep 2026

Medicines, misinformation and machines: Navigating infodemics in the generative AI era.

A two-layer framework is proposed that separates assessment of a claim's evidentiary status from action on its distribution across digital platforms and would identify claims that warrant rapid assessment and, where necessary, proportionate and time-limited intervention.

Natansh D. Modi, L. K. Kalisch Ellett, Michael D. Wiese et al. · 0 citations
#generative ai Preprint Sep 2026

Auditing Patient Privacy in Medical Generative Models: Scalable Memorization Detection with DeepSSIM++

DeepSSIM++ is introduced, a self-supervised similarity metric for scalable memorization auditing in medical generative models that accelerates large-scale similarity computation by several orders of magnitude compared with analytical SSIM.

Antonio Scardace, Francesco Guarnera, Sebastiano Battiato et al. · 0 citations
#generative ai Open access Sep 2026

Trusting the Algorithm: Exploring Higher Educators' Confidence in Generative AI Tools for Academic Assistance

The rapid diffusion of generative artificial intelligence (GenAI) in higher education is transforming academic teaching, research, and administrative practices while simultaneously challenging institutional structures for governance, professional development, and academic integrity. Despite the growing use of GenAI too...

Manal Hamarsha · 0 citations
#generative ai Open access Sep 2026

ACTA Brief 01 — The Evidence Gap: When AI Classification Determines Royalties, Visibility and Eligibility, What Evidence Does an Artist Have?

Between June and September 2026 the recorded-music industry adopted, in rapid succession, a set of instruments for handling AI-generated and AI-assisted music: automated detection with economic consequences (TIDAL, July 15), industry-wide voluntary labels (IFPI, RIAA and partners, July 10), platform-side disclosure and...

Elodie P. Remoissenet · 0 citations
#generative ai Open access Sep 2026

How Much Measurement Does an AI Visibility Claim Need? Replicate Instability and Minimum Detectable Effects in Generative Search Audits

A commercial category now sells businesses a measurement of how often generative search engines cite them, typically from a few dozen prompts sampled once. We ask what such a measurement can actually support. Using 4,320 observations in which identical queries were issued three times to each of four generative answer s...

Muhammad Arshad · 0 citations
#generative ai Open access Sep 2026

Explainable Deep Generative Models with Adversarial Sample Defense

Deep generative models have achieved remarkable success in various domains, including image generation, text generation, and music generation. However, these models often operate as black boxes, lacking transparency and interpretability. Furthermore, they are highly vulnerable to adversarial attacks, where subtle pertu...

Jincheng Zhang · 0 citations
#generative ai Open access Sep 2026

Computational Creativity via Generative Process Modeling

This paper explores the development of a novel approach to computational creativity centered around generative process modeling. Current AI systems striving for creative output frequently fall short of mimicking the nuanced and often unpredictable nature of human creativity. A key limitation is the absence of a mechani...

Jincheng Zhang · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

Microsoft Research Blog Oct 22, 2026

Flint-interactive: A language for creating interactive data visualizations

Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.

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