Generative artificial intelligence: Implications and considerations for higher education practice

T Farrelly, N Baker - Education Sciences, 2023 - mdpi.com
Generative Artificial Intelligence (GAI) has emerged as a transformative force in higher
education, offering both challenges and opportunities. This paper explores the multifaceted …

Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense

K Krishna, Y Song, M Karpinska… - Advances in Neural …, 2024 - proceedings.neurips.cc
The rise in malicious usage of large language models, such as fake content creation and
academic plagiarism, has motivated the development of approaches that identify AI …

Authorship attribution in the era of llms: Problems, methodologies, and challenges

B Huang, C Chen, K Shu - arXiv preprint arXiv:2408.08946, 2024 - arxiv.org
Accurate attribution of authorship is crucial for maintaining the integrity of digital content,
improving forensic investigations, and mitigating the risks of misinformation and plagiarism …

A survey on llm-gernerated text detection: Necessity, methods, and future directions

J Wu, S Yang, R Zhan, Y Yuan, DF Wong… - arXiv preprint arXiv …, 2023 - arxiv.org
The powerful ability to understand, follow, and generate complex language emerging from
large language models (LLMs) makes LLM-generated text flood many areas of our daily …

A survey on detection of llms-generated content

X Yang, L Pan, X Zhao, H Chen, L Petzold… - arXiv preprint arXiv …, 2023 - arxiv.org
The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT
have led to an increase in synthetic content generation with implications across a variety of …

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 …

User modeling in the era of large language models: Current research and future directions

Z Tan, M Jiang - arXiv preprint arXiv:2312.11518, 2023 - arxiv.org
User modeling (UM) aims to discover patterns or learn representations from user data about
the characteristics of a specific user, such as profile, preference, and personality. The user …

Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset

S Alavi Naeini, R Saqur, M Saeidi… - Advances in Neural …, 2024 - proceedings.neurips.cc
The quest for human imitative AI has been an enduring topic in AI research since inception.
The technical evolution and emerging capabilities of the latest cohort of large language …

Gender, age, and technology education influence the adoption and appropriation of LLMs

F Draxler, D Buschek, M Tavast, P Hämäläinen… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) such as ChatGPT have become increasingly integrated into
critical activities of daily life, raising concerns about equitable access and utilization across …

Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integrity

S Pudasaini, L Miralles-Pechuán, D Lillis… - arXiv preprint arXiv …, 2024 - arxiv.org
The rise of Large Language Models (LLMs) such as ChatGPT and Gemini has posed new
challenges for the academic community. With the help of these models, students can easily …