Results 11 to 20 of about 106,494 (293)

Densing law of LLMs [PDF]

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
core   +5 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.
Rozado, David
core   +6 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

Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques [PDF]

This paper explores the potential use of Large Language Models (LLMs), such as ChatGPT, Google Gemini, and Microsoft Copilot, in threat hunting, specifically focusing on Living off the Land (LotL) techniques.
Politis, Ilias, William J. Buchanan, Buchanan, William J., Konstantinou, Antreas, Ilias Politis, Pitropakis, Nikolaos, Jawad Ahmad, Dimitrios Kasimatis, Kasimatis, Dimitrios, Sana Ullah Jan, Antreas Konstantinou, Nikolaos Pitropakis, Ullah Jan, Sana, Ahmad, Jawad   +13 more
core   +1 more source

Large Language Models and Privacy in the Corporate Context

European Journal of Privacy Law & Technologies
The rapid development of Large Language Models (LLMs), such as GPT-3 and GPT-4, has transformed corporate functions, yet their integration raises critical privacy concerns.
Guendalina Capece, Lucilla Gatt, Vittoria Bonino   +2 more
doaj   +1 more source

"To LLM, or Not to LLM?": How Designers and Developers Navigate LLMs as Tools or Teammates

Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems
6 pages, 2 figures, 1 ...
Varad Vishwarupe, Ivan Flechais, Nigel Shadbolt, Marina Denise Jirotka   +3 more
openaire   +2 more sources

PARAMETER EFFICIENT FINE-TUNING AND OVERFITTING IN GPT LARGE LANGUAGE MODELS: A METRIC-BASED COMPARISON

Електроніка та інформаційні технології
Background. Building upon previous research, this study conducts an exploration into Large Language Models (LLMs), with an emphasis on the fine-tuning and assessment of LLaMA-3.1 for instructional tasks. LLaMA-3.1, which is a new generation model and has
Bohdan Pavlyshenko, Ivan Bulka
doaj   +1 more source

LLMs + Persona-Plug = Personalized LLMs

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Personalization plays a critical role in numerous language tasks and applications, since users with the same requirements may prefer diverse outputs based on their individual interests. This has led to the development of various personalized approaches aimed at adapting large language models (LLMs) to generate customized outputs aligned with user ...
Jiongnan Liu 0001, Yutao Zhu 0001, Shuting Wang 0002, Xiaochi Wei, Erxue Min, Yu Lu 0009, Shuaiqiang Wang, Dawei Yin 0001, Zhicheng Dou   +8 more
openaire   +4 more sources

Machine Learning or Human Education? Thoughts and Data on Artificial Intelligence and the Labor Market: Economic Sociological Aspects of Career Orientation.

Fogyatékosság és Társadalom
The economic trends reviewed in this paper will play a prominent role in the labor market of the near future with the exponential growth of the uptake of artificial intelligence applications.
Keszi, Roland
doaj   +1 more source

Set-LLM: A Permutation-Invariant LLM

CoRR
While large language models (LLMs) demonstrate impressive capabilities across numerous applications, their robustness remains a critical concern. This paper is motivated by a specific vulnerability: the order sensitivity of LLMs. This vulnerability manifests itself as the order bias observed when LLMs decide between possible options (for example, a ...
Beni Egressy, Jan Stühmer
openaire   +3 more sources