April 15, 2024, 4:47 a.m. | Areg Mikael Sarvazyan, Jos\'e \'Angel Gonz\'alez, Marc Franco-Salvador

cs.CL updates on arXiv.org arxiv.org

arXiv:2401.03946v2 Announce Type: replace
Abstract: Recent advancements in Large Language Models (LLMs) have led to high-quality Machine-Generated Text (MGT), giving rise to countless new use cases and applications. However, easy access to LLMs is posing new challenges due to misuse. To address malicious usage, researchers have released datasets to effectively train models on MGT-related tasks. Similar strategies are used to compile these datasets, but no tool currently unifies them. In this scenario, we introduce TextMachina, a modular and extensible Python …

abstract access applications arxiv cases challenges cs.cl datasets easy generated giving however language language models large language large language models llms machine misuse quality researchers text train type usage use cases

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