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On the Effects of Fine-tuning Language Models for Text-Based Reinforcement Learning
Moreover, we describe the occurrence of semantic degeneration as a consequence of inappropriate fine-tuning of language models in text-based reinforcement learning (TBRL).
An Exploration of Unreliable News Classification in Brazil and The U.S
Our results show that features related to the writing style were prominent in both data sets and, despite the language difference, some features have a universal behavior, being significant to both US and Brazilian news articles.
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