Artificial intelligence is accelerating materials discovery, yet for complex systems such as high-entropy alloys, exhaustive exploration of their immense composition spaces is computationally intractable. Here we propose an integrated framework that enables large-scale exploration with reduced resource demands. Our f...
Xiao-Ya Huang, Yu Liu, Shuo Shi et al.· Nature Communications· 0 citations
Recent advances in artificial intelligence (AI) have largely been driven by large language models, deep neural networks that operate over discrete units called tokens. To represent text, most large language models use words or word fragments as the tokens, known as subword tokenization1. Subword tokenization obscures f...
Benjamin Minixhofer, Tyler Murray, Tomasz Limisiewicz et al.· Nature· 1 citation
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.· Zenodo (CERN European Organi...· 0 citations
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...
Hong Sun· International journal of soc...· 0 citations
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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.· SN Business & Economics· 8 citations
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.· Discover Education· 0 citations
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
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
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
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...
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
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
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
