3 citations · 4 across the 6 of their papers we have counts for
6 papers
MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection
Arkadiusz Modzelewski, Witold Sosnowski, Eleni Papadopulos +4
The intentional creation and spread of disinformation poses a significant threat to public discourse. However, existing English datasets and research rarely address the intentional…
PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformation
Arkadiusz Modzelewski, Witold Sosnowski, Tiziano Labruna +2
Disinformation detection is a key aspect of media literacy. Psychological studies have shown that knowledge of persuasive fallacies helps individuals detect disinformation. Inspire…
Revisiting Distance Metric Learning for Few-Shot Natural Language Classification
Witold Sosnowski, Anna Wróblewska, Karolina Seweryn +1
Distance Metric Learning (DML) has attracted much attention in image processing in recent years. This paper analyzes its impact on supervised fine-tuning language models for Natura…
Distance Metric Learning Loss Functions in Few-Shot Scenarios of Supervised Language Models Fine-Tuning
Witold Sosnowski, Karolina Seweryn, Anna Wróblewska +1
This paper presents an analysis regarding an influence of the Distance Metric Learning (DML) loss functions on the supervised fine-tuning of the language models for classification…
TASTEset -- Recipe Dataset and Food Entities Recognition Benchmark
Ania Wróblewska, Agnieszka Kaliska, Maciej Pawłowski +3
Food Computing is currently a fast-growing field of research. Natural language processing (NLP) is also increasingly essential in this field, especially for recognising food entiti…
Applying SoftTriple Loss for Supervised Language Model Fine Tuning
Witold Sosnowski, Anna Wroblewska, Piotr Gawrysiak
We introduce a new loss function TripleEntropy, to improve classification performance for fine-tuning general knowledge pre-trained language models based on cross-entropy and SoftT…