Results 71 to 80 of about 520,319 (211)

Personality Emulation Utilizing Large Language Models

Applied Sciences
Fake identities have proven to be an effective methodology for conducting privacy and cybersecurity research; however, existing models are limited in their ability to interact with and respond to received communications.
Jack Kolenbrander, Alan J. Michaels
doaj   +1 more source

Large Body Language Models

CoRR
As virtual agents become increasingly prevalent in human-computer interaction, generating realistic and contextually appropriate gestures in real-time remains a significant challenge. While neural rendering techniques have made substantial progress with static scripts, their applicability to human-computer interactions remains limited. To address this,
Saif Punjwani, Larry Heck
openaire   +2 more sources

Optimizing Large Language Models: Bridging Performance and Efficiency with Knowledge Distillation [PDF]

Large language models (LLMs) have revolutionized natural language processing (NLP), demonstrating remarkable capabilities in tasks such as text generation, reasoning, and understanding.
Tina, Clementina, Ursula, Sajjad, Idowu, Callixtus   +2 more
core   +1 more source

Steganography with Large Language Models

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Large language model (LLM) steganography generates fluent cover text that encodes a secret message, with the secret key often given as a natural language prompt or seed.
Alexander V Mantzaris, Wissam Ghantous, Haley Stinebrickner, Samira Jahangiri, Stephen Webinga   +4 more
doaj  

Enhancing Review-based Recommender Systems with Attention-driven Models Leveraging Large Language Model's Embeddings [PDF]

, 2023
LAUREA MAGISTRALEQuesta tesi ha lo scopo di riempire un'attuale lacuna nel mondo dei recommender systems. Esistono infatti numerose tecniche che sfruttano le recensioni lasciate da utenti a prodotti come informazione aggiuntiva per arricchire le ...
Marragony, Salvatore
core  

Human languaging and large language models

AI & SOCIETY
Abstract This paper explores the interplay between human languaging and AI-powered language models from the view of the distributed language perspective (DLP). According to this perspective, human linguistic activity can be described as ongoing, heterogenous activity, thus making proponents of DLP prefer the term ‘languaging’ to that ...
openaire   +2 more sources

Modeling meets Large Language Models

Modeling business processes is often challenging due to its complexity and potential for errors. One key issue arises when process experts and modelers are different individuals, which can lead to communication gaps and result in low-quality business process models.
Martin Forell, Selina Schüler
openaire   +2 more sources

Large Language Models in Healthcare

CoRR
Large language models (LLMs) hold promise for transforming healthcare, from streamlining administrative and clinical workflows to enriching patient engagement and advancing clinical decision-making. However, their successful integration requires rigorous development, adaptation, and evaluation strategies tailored to clinical needs.
Mohammed Ali Al-Garadi, Tushar Mungle, Abdulaziz Ahmed, Abeed Sarker, Zhuqi Miao, Michael E. Matheny   +5 more
openaire   +2 more sources

Large Language Models and Male Circumcision: A Reliability Assessment [PDF]

Aim: Male circumcision remains routine in some countries for neonatal or religious reasons; however, it continues to be the subject of ongoing debate concerning its health benefits, potential risks, and implications for bodily autonomy.
Ibrahim Hacibey, Ismail Ulus, Gokhan Ceker   +2 more
core   +1 more source

Large Language Models for Manufacturing

CoRR
The rapid advances in Large Language Models (LLMs) have the potential to transform manufacturing industry, offering new opportunities to optimize processes, improve efficiency, and drive innovation. This paper provides a comprehensive exploration of the integration of LLMs into the manufacturing domain, focusing on their potential to automate and ...
Yiwei Li 0002, Huaqin Zhao, Hanqi Jiang, Yi Pan 0001, Zhengliang Liu, Zihao Wu 0001, Peng Shu, Jie Tian, Tianze Yang, Shaochen Xu, Yanjun Lyu, Parker Blenk, Jacob Pence, Jason Rupram, Eliza Banu, Ninghao Liu 0001, Linbing Wang, Wen-Zhan Song 0001, Xiaoming Zhai, Kenan Song, Dajiang Zhu, Beiwen Li, Xianqiao Wang, Tianming Liu 0001   +23 more
openaire   +2 more sources