Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Moro, Róbert"'
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 however mostly focused on the English language and longer texts, such as
Externí odkaz:
http://arxiv.org/abs/2406.12549
Autor:
Macko, Dominik, Moro, Robert, Uchendu, Adaku, Srba, Ivan, Lucas, Jason Samuel, Yamashita, Michiharu, Tripto, Nafis Irtiza, Lee, Dongwon, Simko, Jakub, Bielikova, Maria
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-generated text (MGT) detection is important to cope with such threats. H
Externí odkaz:
http://arxiv.org/abs/2401.07867
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 disinformation content might have dramatic consequences for societies a
Externí odkaz:
http://arxiv.org/abs/2311.08838
Autor:
Tripto, Nafis Irtiza, Venkatraman, Saranya, Macko, Dominik, Moro, Robert, Srba, Ivan, Uchendu, Adaku, Le, Thai, Lee, Dongwon
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 each of
Externí odkaz:
http://arxiv.org/abs/2311.08374
This study compares the performance of (1) fine-tuned models and (2) extremely large language models on the task of check-worthy claim detection. For the purpose of the comparison we composed a multilingual and multi-topical dataset comprising texts
Externí odkaz:
http://arxiv.org/abs/2311.06121
Autor:
Macko, Dominik, Moro, Robert, Uchendu, Adaku, Lucas, Jason Samuel, Yamashita, Michiharu, Pikuliak, Matúš, Srba, Ivan, Le, Thai, Lee, Dongwon, Simko, Jakub, Bielikova, Maria
Publikováno v:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
There is a lack of research into capabilities of recent LLMs to generate convincing text in languages other than English and into performance of detectors of machine-generated text in multilingual settings. This is also reflected in the available ben
Externí odkaz:
http://arxiv.org/abs/2310.13606
Autor:
Pikuliak, Matúš, Srba, Ivan, Moro, Robert, Hromadka, Timo, Smolen, Timotej, Melisek, Martin, Vykopal, Ivan, Simko, Jakub, Podrouzek, Juraj, Bielikova, Maria
Publikováno v:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
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 content being investigated. This paper introduces a new multilingual da
Externí odkaz:
http://arxiv.org/abs/2305.07991
Eye tracking in recommender systems can provide an additional source of implicit feedback, while helping to evaluate other sources of feedback. In this study, we use eye tracking data to inform a collaborative filtering model for movie recommendation
Externí odkaz:
http://arxiv.org/abs/2305.07516
To mitigate the negative effects of false information more effectively, the development of Artificial Intelligence (AI) systems assisting fact-checkers is needed. Nevertheless, the lack of focus on the needs of these stakeholders results in their lim
Externí odkaz:
http://arxiv.org/abs/2211.12143
Autor:
Srba, Ivan, Moro, Robert, Tomlein, Matus, Pecher, Branislav, Simko, Jakub, Stefancova, Elena, Kompan, Michal, Hrckova, Andrea, Podrouzek, Juraj, Gavornik, Adrian, Bielikova, Maria
Publikováno v:
ACM Transactions on Recommender Systems. 1, 1, Article 6 (March 2023), 33 pages
In this paper, we present results of an auditing study performed over YouTube aimed at investigating how fast a user can get into a misinformation filter bubble, but also what it takes to "burst the bubble", i.e., revert the bubble enclosure. We empl
Externí odkaz:
http://arxiv.org/abs/2210.10085