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artificial intelligence

14,159 papers

#artificial intelligence Book Open access Oct 2026

Precision Dosing, Adaptive Algorithms and AI driven Prescribing

Personalized drug exposure The concept of precision dosing is the next generation of drug-based therapy, which stops at a stereotyped regimen and gets triggered by targeted biological, clinical, and digital data streams that are unique to each patient. The use of pharmacometrics, real-time therapeutic drug monitoring,...

Rajan Ethiraj Ugandar, Rangu Naga Sai Sindhuja, Regati Pujitha Reddy et al. · 0 citations
#artificial intelligence Open access Oct 2026

Artificial Intelligence Capability and Enterprise Innovation Performance: The Mediating Role of Knowledge Sharing and the Moderating Role of Environmental Dynamism

Artificial intelligence (AI) is becoming an enterprise-level capability rather than a stand-alone technology, but firms differ substantially in their ability to convert AI resources into sustained innovation performance. This study proposes a conditional process model in which AI capability enhances enterprise innovati...

Sun Hong · 0 citations
#artificial intelligence Review Open access Oct 2026

AI in supply chain risk assessment: a systematic literature review and bibliometric analysis

Abstract Supply chain risk assessment (SCRA) is pivotal for ensuring resilience in increasingly complex global supply networks. While existing reviews have explored traditional methodologies, they often neglect emerging artificial intelligence (AI) and machine learning (ML) applications and mostly lack combined systema...

Md Abrar Jahin, Saleh Akram Naife, Anik Saha et al. · 8 citations
#artificial intelligence Open access Oct 2026

Integration of ChatGPT to enhance English speaking skills among secondary school students in Pakistan

The integration of Artificial Intelligence (AI) into education is expanding rapidly, particularly in language learning. This study evaluated the effectiveness of a ChatGPT-assisted learning module in enhancing English-speaking proficiency in terms of range, accuracy, fluency, interaction, and coherence among secondary...

Sobia Nageen, Hisham Ul Hasan Khawaja, Muhammad Sarwar et al. · 0 citations
#artificial intelligence Preprint Aug 2026

Sign Language Video Synthesis via Loss-Guided Multi-Expert GANs

This preliminary technical report presents a framework for sign language video synthesis using a loss-guided multi-expert Generative Adversarial Network (GAN) to enhance communication for individuals with hearing impairments. Three specialized discriminators--global, hand, and head--each guide a corresponding expert br...

Ding-Zhan Nong, Zhi-Hao Ren, Ziqi Li et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

ModPack: Extensible Teleoperation Interface for Bimanual Mobile Manipulation

Existing teleoperation systems are often tailored to specific robot hardware and task domains, limiting their scalability and adaptability. We present ModPack, a modular and extensible teleoperation system designed to support diverse robot embodiments and task requirements within a unified framework. At the core of Mod...

Joshua Citron, Renee Zbizika, Zeyi Liu et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Adapting Generalist Vehicle Models for High-Speed MPC Across Terrains

High-speed off-road autonomy requires precise closed-loop control for a target vehicle while remaining robust across changing terrains. Recent forward kinodynamic (FKD) prediction foundation models suggest a promising path, starting from a generalist model and specializing it to the target platform. However, effective...

Rwik Rana, Jesse Quattrociocchi, Christian Ellis et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

FAR: Failure-Aware Retry for Test-Time Recovery and Continual Policy Improvement

Robot policies inevitably encounter failures when deployed in real environments. Naive retries often repeat the same mistakes, while many existing recovery methods rely on human intervention. In this paper, we propose Failure-Aware Retry (FAR), a framework that enables robots to learn from previous failures at test tim...

Haoran Hao, Shahram Najam Syed, Jeffrey Ichnowski et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Curvature-Guided Module Localization for Low-Rank Detoxification of Backdoored Large Language Models

Backdoor attacks pose a serious threat to large language models (LLMs) by causing otherwise benign systems to produce attacker-specified malicious behavior when a hidden trigger is present. In this work, we study post hoc detoxification of backdoored LLMs in a practical setting where the defender has access to the pois...

Arash Raftari, Mehrdad Mahdavi, Nathan Blackthorn et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

AI-Assisted Computational Reproducibility on the FABRIC Testbed

Computational reproducibility remains difficult despite being central to scientific research. In this paper, we show how the international FABRIC testbed, combined with a large language model (LLM) coding agent through LoomAI, can simplify reproducing published experiments across multiple domains. We reproduced three c...

Komal Thareja, Paul Ruth, Berent Aldikacti et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Geological text descriptions in ill-posed inverse problems: insights from learned hydraulic-conductivity inversion

Hydraulic-conductivity inversion is ill posed: even complete head observations can leave structural ambiguity. Geological text descriptions can supply additional information about subsurface structure to constrain reconstruction. However, it remains unclear when descriptions improve reconstruction and how solvers use t...

Taiga Saito, Yu Otake, Daijiro Mizutani et al. · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Walk fast but be careful: Understanding Parallel Sampling in Masked Diffusion

In this paper, we use random walks on graphs as a verifiable sandbox for studying parallel sampling strategies in masked diffusion models (MDMs). We train an MDM on random walk samples from a fixed graph. The graph and transition kernel are never shown to the model and serve as latent structure that is both controllabl...

Vansh Bansal, Cholyeon Cho, Syamantak Kumar et al. · 0 citations

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MIT News · Artificial Intelligence Sep 29, 2026

Who we become when we talk to machines

Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.

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