Publications

Whether AI leads to better journalism is an ongoing debate, but more media companies across the world aren’t waiting to find out which side up new tech lands. The media sector is jumping on the trend and embracing the latest… Read More »The rise and integration of artificial intelligence into our daily lives is no longer a futuristic fantasy, but new data shows AI in the media sector might do more harm than good.

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 »A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts

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 »KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection

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 »SIDBench: A Python framework for reliably assessing synthetic image detection methods

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 »Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation