Creators:Macko, Dominik Moro, Robert Uchendu, Adaku Srba, Ivan Lucas, Jason Samuel Yamashita, Michiharu Tripto, Nafis Irtiza Simko, Jakub Bielikova, Maria Description: High-quality text generation capability of latest Large Language Models (LLMs) causes concerns about their misuse (e.g., in … Read More
Scientific Publications
A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts
Creators Description: In the realm of text manipulation and linguistic transformation, the question of authorship has been a subject of fascination and philosophical inquiry. Much like the Ship of Theseus paradox, which ponders whether a ship remains the same when … Read More
KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection
Creators: Description: SemEval-2024 Task 8 is focused on multigenerator, multidomain, and multilingual black-box machine-generated text detection. Such a detection is important for preventing a potential misuse of large language models (LLMs), the newest of which are very capable in generating … Read More
SIDBench: A Python framework for reliably assessing synthetic image detection methods
Creators Description The generative AI technology offers an increasing variety of tools for generating entirely synthetic images that are increasingly indistinguishable from real ones. Unlike methods that alter portions of an image, the creation of completely synthetic images presents a … Read More
Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation
Creators Description The latest generative large language models (LLMs) have found their application in data augmentation tasks, where small numbers of text samples are LLM-paraphrased and then used to fine-tune downstream models. However, more research is needed to assess how … Read More