57 citations · 214 across the 21 of their papers we have counts for
12 papers · 1 filter
MultiCW: A Large-Scale Balanced Benchmark Dataset for Training Robust Check-Worthiness Detection Models
Martin Hyben, Sebastian Kula, Jan Cegin +3
Large Language Models (LLMs) are beginning to reshape how media professionals verify information, yet automated support for detecting check-worthy claims a key step in the fact-che…
Increasing the Robustness of the Fine-tuned Multilingual Machine-Generated Text Detectors
Dominik Macko, Robert Moro, Ivan Srba
Since the proliferation of LLMs, there have been concerns about their misuse for harmful content creation and spreading. Recent studies justify such fears, providing evidence of LL…
Beyond speculation: Measuring the growing presence of LLM-generated texts in multilingual disinformation
Dominik Macko, Aashish Anantha Ramakrishnan, Jason Samuel Lucas +4
Increased sophistication of large language models (LLMs) and the consequent quality of generated multilingual text raises concerns about potential disinformation misuse. While huma…
Evaluation of LLM Vulnerabilities to Being Misused for Personalized Disinformation Generation
Aneta Zugecova, Dominik Macko, Ivan Srba +4
The capabilities of recent large language models (LLMs) to generate high-quality content indistinguishable by humans from human-written texts raises many concerns regarding their m…
A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Models
Ivan Srba, Olesya Razuvayevskaya, João A. Leite +10
In the age of social media and generative AI, the ability to automatically assess the credibility of online content has become increasingly critical, complementing traditional appr…
MultiSocial: Multilingual Benchmark of Machine-Generated Text Detection of Social-Media Texts
Dominik Macko, Jakub Kopal, Robert Moro +1
Recent LLMs are able to generate high-quality multilingual texts, indistinguishable for humans from authentic human-written ones. Research in machine-generated text detection is ho…
Authorship Obfuscation in Multilingual Machine-Generated Text Detection
Dominik Macko, Robert Moro, Adaku Uchendu +7
High-quality text generation capability of recent Large Language Models (LLMs) causes concerns about their misuse (e.g., in massive generation/spread of disinformation). Machine-ge…
Disinformation Capabilities of Large Language Models
Ivan Vykopal, Matúš Pikuliak, Ivan Srba +3
Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with d…
A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts
Nafis Irtiza Tripto, Saranya Venkatraman, Dominik Macko +5
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 These…
Multilingual and Multi-topical Benchmark of Fine-tuned Language models and Large Language Models for Check-Worthy Claim Detection
Martin Hyben, Sebastian Kula, Ivan Srba +2
This study compares the performance of (1) fine-tuned language models and (2) large language models on the task of check-worthy claim detection. For the purpose of the comparison w…
Multilingual Previously Fact-Checked Claim Retrieval
Matúš Pikuliak, Ivan Srba, Robert Moro +7
Fact-checkers are often hampered by the sheer amount of online content that needs to be fact-checked. NLP can help them by retrieving already existing fact-checks relevant to the c…
Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims
Ivan Srba, Branislav Pecher, Matus Tomlein +4
False information has a significant negative influence on individuals as well as on the whole society. Especially in the current COVID-19 era, we witness an unprecedented growth of…