Security and privacy on generative data in aigc: A survey

T Wang, Y Zhang, S Qi, R Zhao, Z **a… - ACM Computing Surveys, 2024 - dl.acm.org
The advent of artificial intelligence-generated content (AIGC) represents a pivotal moment in
the evolution of information technology. With AIGC, it can be effortless to generate high …

The impact of AI in physics education: a comprehensive review from GCSE to university levels

W Yeadon, T Hardy - Physics Education, 2024 - iopscience.iop.org
With the rapid evolution of artificial intelligence (AI), its potential implications for higher
education have become a focal point of interest. This study delves into the capabilities of AI …

A survey on LLM-generated text detection: Necessity, methods, and future directions

J Wu, S Yang, R Zhan, Y Yuan, LS Chao… - Computational …, 2025 - direct.mit.edu
The remarkable ability of large language models (LLMs) to comprehend, interpret, and
generate complex language has rapidly integrated LLM-generated text into various aspects …

Detecting multimedia generated by large ai models: A survey

L Lin, N Gupta, Y Zhang, H Ren, CH Liu, F Ding… - arxiv preprint arxiv …, 2024 - arxiv.org
The rapid advancement of Large AI Models (LAIMs), particularly diffusion models and large
language models, has marked a new era where AI-generated multimedia is increasingly …

Gpt-who: An information density-based machine-generated text detector

S Venkatraman, A Uchendu, D Lee - arxiv preprint arxiv:2310.06202, 2023 - arxiv.org
The Uniform Information Density (UID) principle posits that humans prefer to spread
information evenly during language production. We examine if this UID principle can help …

Securing large language models: Threats, vulnerabilities and responsible practices

S Abdali, R Anarfi, CJ Barberan, J He - arxiv preprint arxiv:2403.12503, 2024 - arxiv.org
Large language models (LLMs) have significantly transformed the landscape of Natural
Language Processing (NLP). Their impact extends across a diverse spectrum of tasks …

Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges

P Kumar - International Journal of Multimedia Information …, 2024 - Springer
Large language models (LLMs) have exhibited remarkable efficacy and proficiency in a
wide array of NLP endeavors. Nevertheless, concerns are growing rapidly regarding the …

[HTML][HTML] A benchmark dataset to distinguish human-written and machine-generated scientific papers

MHI Abdalla, S Malberg, D Dementieva, E Mosca… - Information, 2023 - mdpi.com
As generative NLP can now produce content nearly indistinguishable from human writing, it
is becoming difficult to identify genuine research contributions in academic writing and …

Decoding the ai pen: Techniques and challenges in detecting ai-generated text

S Abdali, R Anarfi, CJ Barberan, J He - Proceedings of the 30th ACM …, 2024 - dl.acm.org
Large Language Models (LLMs) have revolutionized the field of Natural Language
Generation (NLG) by demonstrating an impressive ability to generate human-like text …

A survey of ai-generated text forensic systems: Detection, attribution, and characterization

T Kumarage, G Agrawal, P Sheth, R Moraffah… - arxiv preprint arxiv …, 2024 - arxiv.org
We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs)
capable of generating high-quality text. While these LLMs have revolutionized text …