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pro vyhledávání: '"Ebrahimi, Seyedeh Fatemeh"'
Autor:
Ebrahimi, Seyedeh Fatemeh, Azari, Karim Akhavan, Iravani, Amirmasoud, Alizadeh, Hadi, Taghavi, Zeinab Sadat, Sameti, Hossein
Publikováno v:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Semantic Textual Relatedness holds significant relevance in Natural Language Processing, finding applications across various domains. Traditionally, approaches to STR have relied on knowledge-based and statistical methods. However, with the emergence
Externí odkaz:
http://arxiv.org/abs/2407.12426
Autor:
Ebrahimi, Seyedeh Fatemeh, Azari, Karim Akhavan, Iravani, Amirmasoud, Qazvini, Arian, Sadeghi, Pouya, Taghavi, Zeinab Sadat, Sameti, Hossein
Detecting Machine-Generated Text (MGT) has emerged as a significant area of study within Natural Language Processing. While language models generate text, they often leave discernible traces, which can be scrutinized using either traditional feature-
Externí odkaz:
http://arxiv.org/abs/2407.11774