Results 71 to 80 of about 26,588 (249)

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

LLM-Select: Feature Selection with Large Language Models

Trans. Mach. Learn. Res.
In this paper, we demonstrate a surprising capability of large language models (LLMs): given only input feature names and a description of a prediction task, they are capable of selecting the most predictive features, with performance rivaling the standard tools of data science.
Daniel P. Jeong, Zachary C. Lipton, Pradeep Ravikumar   +2 more
openaire   +4 more sources

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source

Multi-Criteria Evaluation of Large Language Models (LLMs): Balancing Performance and Security

IEEE Access
Because of their functionality and practicality, Large Language Models (LLMs) have been widely discussed, with a large number of benchmarks being conducted to evaluate them, especially their efficiency levels. However, despite their numerous applications
Daniel Mendonca Colares, Placido Rogerio Pinheiro, Raimir Holanda Filho   +2 more
doaj   +1 more source

Large Language Models (LLMs): Deployment, Tokenomics and Sustainability

CoRR
The rapid advancement of Large Language Models (LLMs) has significantly impacted human-computer interaction, epitomized by the release of GPT-4o, which introduced comprehensive multi-modality capabilities. In this paper, we first explored the deployment strategies, economic considerations, and sustainability challenges associated with the state-of-the ...
Haiwei Dong 0001, Shuang Xie
openaire   +3 more sources

A Perspective on Interactive Theorem Provers in Physics

Advanced Science, EarlyView.
Into an interactive theorem provers (ITPs), one can write mathematical definitions, theorems and proofs, and the correctness of those results is automatically checked. This perspective goes over the best usage of ITPs within physics and motivates the open‐source community run project PhysLean, the aim of which is to be a library for digitalized physics
Joseph Tooby‐Smith
wiley   +1 more source

Applying large language models for automated essay scoring for non-native Japanese

Humanities & Social Sciences Communications
Recent advancements in artificial intelligence (AI) have led to an increased use of large language models (LLMs) for language assessment tasks such as automated essay scoring (AES), automated listening tests, and automated oral proficiency assessments ...
Wenchao Li, Haitao Liu
doaj   +1 more source

BatGPT-Chem: A Foundation Large Model for Chemical Engineering

Research
Large language models (LLMs) have showcased remarkable capabilities in the realm of AI for Science, and chemistry has greatly benefited from the advancement of AI tools.
Yifei Yang, Runhan Shi, Zuchao Li, Shu Jiang, Bao-Liang Lu, Qibin Zhao, Yang Yang, Hai Zhao   +7 more
doaj   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source