Results 1 to 10 of about 55,072 (308)

Densing law of LLMs

Nature Machine Intelligence
Abstract Large language models (LLMs) have emerged as a milestone in artificial intelligence. The scaling law indicates that the performance of LLMs can continually improve as the model size increases, which poses challenges for training and deployment.
Chaojun Xiao, Jie Cai, Weilin Zhao, Biyuan Lin, Guoyang Zeng, Jie Zhou, Zhi Zheng, Xu Han, Zhiyuan Liu, Maosong Sun   +9 more
openaire   +3 more sources

The political preferences of LLMs

PLOS ONE
I report here a comprehensive analysis about the political preferences embedded in Large Language Models (LLMs). Namely, I administer 11 political orientation tests, designed to identify the political preferences of the test taker, to 24 state-of-the-art conversational LLMs, both closed and open source.
David Rozado
openaire   +5 more sources

Can LLMs be Fooled? Investigating Vulnerabilities in LLMs

CoRR
14 pages, 1 figure.
Sara Abdali, Jia He, C. J. Barberan, Richard Anarfi   +3 more
openaire   +3 more sources

Trends and challenges of Arabic Chatbots: Literature review

Jordanian Journal of Computers and Information Technology, 2023
A conversational system is a natural language processing task that has recently attracted increasing attention with the advancements in Large Language Models (LLMs) and Language Models for Dialogue Applications (LaMDA). However, Conversational Artificial
Yassine Saoudi, Mohamed Mohsen Gammoudi
doaj   +1 more source

The LLM Surgeon

CoRR, 2023
State-of-the-art language models are becoming increasingly large in an effort to achieve the highest performance on large corpora of available textual data. However, the sheer size of the Transformer architectures makes it difficult to deploy models within computational, environmental or device-specific constraints.
Tycho F. A. van der Ouderaa, Markus Nagel, Mart van Baalen, Yuki M. Asano, Tijmen Blankevoort   +4 more
openaire   +2 more sources

LLM magnons [PDF]

Journal of High Energy Physics, 2016
We consider excitations of LLM geometries described by coloring the LLM plane with concentric black rings. Certain closed string excitations are localized at the edges of these rings. The string theory predictions for the energies of magnon excitations of these strings depends on the radii of the edges of the rings.
de Mello Koch, R., Mathwin, C., Van Zyl, H.J.R.   +2 more
openaire   +2 more sources

feature-representation-for-LLMs

, 2023
This is a database for feature representation of ESM2, which includes Swiss data, Swiss normalized data, original TrEMBL data, original TrEMBL normalized data, non-homology TrEMBL data and Table S10.Non-homologous TrEMBL normalized data can be created by
yujuan zhang (17148661), Zeyu Luo (8209110), wang rui (17148643)   +2 more
core   +1 more source

Prompt engineering for structured data: a comparative evaluation of styles and LLM performance [PDF]

Artificial Intelligence and Autonomous Systems
Prompt engineering for structured data is an evolving challenge as large language models (LLMs) grow in sophistication. Earlier studies, including prior work by the authors, tested only a limited set of prompts on a single model such as GPT-4o.
Ashraf Elnashar, Jules White, Douglas C. Schmidt   +2 more
doaj   +1 more source

ChatGPT-4 and Italian Dialects: Assessing Linguistic Competence

Umanistica Digitale, 2023
The purpose of this study is to evaluate ChatGPT-4’s language proficiency in Italian dialects. At the outset, it is clarified what is meant by ‘language ability’ within the context of Large Language Models.
Silvia Lilli
doaj   +1 more source

Exploring Alternative Microservice Decompositions using Data-driven Techniques and LLMs

CLEI Electronic Journal
The problem of migrating monolithic applications to microservices has become popular both in industry and academia, particularly when using automated tools to assist developers in the decomposition.
Ana Martínez Saucedo, J. Andres Diaz-Pace, Hernán Astudillo, Guillermo Rodriguez   +3 more
doaj   +1 more source