Results 111 to 120 of about 63,129 (302)

Boosting Large Language Model for Speech Synthesis: An Empirical Study

, 2023
Large language models (LLMs) have made significant advancements in natural language processing and are concurrently extending the language ability to other modalities, such as speech and vision.
Hao, Hongkun, Hu, Shujie, Li, Jinyu, Liu, Shujie, Wang, Rui, Wei, Furu, Zhou, Long   +6 more
core  

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Generative AI for Named Entity Recognition in Low-Resource Language Nepali

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), has significantly advanced Natural Language Processing (NLP) tasks, such as Named Entity Recognition (NER), which involves identifying entities like person, location,
Sameer Neupane, Jeevan Chapagain, Nobal B. Niraula, Diwa Koirala   +3 more
doaj   +1 more source

Examining Differences in Concept Representation Across Similarity Spaces Between Humans and Large Language Models [PDF]

The replication of human concept representation is a critical task for the pursuit of artificial general intelligence. With the recent influx of large language models that demonstrate text-generation capabilities nearly on par with humans, the question ...
Nair, Krishnachandra
core   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models

, 2023
Retrieval-augmented large language models (R-LLMs) combine pre-trained large language models (LLMs) with information retrieval systems to improve the accuracy of factual question-answering.
Deguchi, Jun, Hoshi, Yasuto, Miyashita, Daisuke, Morioka, Yasuhiro, Ng, Youyang, Tatsuno, Kento, Torii, Osamu   +6 more
core  

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

ChatCFD: A Large Language Model‐Driven Agent for End‐to‐End Computational Fluid Dynamics Automation with Structured Knowledge and Reasoning

Advanced Intelligent Discovery, EarlyView.
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan, Kang Hu, Zhuowen Wu, Jiangyang Ge, Jiawei Miao, Yuzhi Zhang, He Sun, Weizong Wang, Tianhan Zhang   +8 more
wiley   +1 more source

Customizing GPT for natural language dialogue interface in database access

Genomics & Informatics
The paper presents Anatomy3DExplorer, a customized ChatGPT designed as a natural language dialogue interface for exploring 3D models of anatomical structures.
Jin-Dong Kim, Kousaku Okubo
doaj   +1 more source

Supervised Knowledge Makes Large Language Models Better In-context Learners

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications.
Bao, Guangsheng, Chen, Weizhu, Wang, Jindong, Wang, Yidong, Xie, Xing, Xu, Ruochen, Yang, Linyi, Ye, Wei, Yu, Zhuohao, Zhang, Shuibai, Zhang, Yue   +10 more
core