Results 81 to 90 of about 239,466 (252)

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

Detecting hallucinations in large language models using semantic entropy

Nature
Large language model (LLM) systems, such as ChatGPT1 or Gemini2, can show impressive reasoning and question-answering capabilities but often ‘hallucinate’ false outputs and unsubstantiated answers3,4.
Sebastian Farquhar, Jannik Kossen, Lorenz Kuhn, Y. Gal   +3 more
semanticscholar   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

An Evaluation of LLMs and Google Translate for Translation of Selected Indian Languages via Sentiment and Semantic Analyses

IEEE Access
Large Language models (LLMs) have been prominent for language translation, including low-resource languages. There has been limited study on the assessment of the quality of translations generated by LLMs, including Gemini, GPT, and Google Translate ...
Rohitash Chandra, Aryan Chaudhari, Yeshwanth Rayavarapu   +2 more
doaj   +1 more source

Farmers’ Protests in Germany: Media Coverage and Types of Bias

Agribusiness, EarlyView.
ABSTRACT The German farmers’ protests of 2024 sparked widespread media coverage and public debate. Yet, media coverage was not always positive, reflecting the media's attention‐seeking and selective focus. Occurrences of farmers blocking media outlets reflected distrust in how their concerns were portrayed.
Felix Schlichte, Doris Läpple
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

Research Progress on the Application of Large Language Model-based Intelligent Medical Assistants

Xiehe Yixue Zazhi
Large language models (LLMs), represented by ChatGPT, have garnered significant attention due to their powerful capabilities in understanding and generating human language.
ZHANG Yuchen, WANG Chuantao, XIA Hailiang, ZHAI Jiliang   +3 more
doaj   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

Aligning large language models and geometric deep models for protein representation

Patterns
Summary: In this study, we explore the alignment of multimodal representations between large language models (LLMs) and geometric deep models (GDMs) in the protein domain. We comprehensively evaluate three LLMs with four protein-specialized GDMs.
Dong Shu, Bingbing Duan, Kai Guo, Kaixiong Zhou, Jiliang Tang, Mengnan Du   +5 more
doaj   +1 more source