반응형 자연어처리572 [2023-02-15] 오늘의 자연어처리 Towards Agile Text Classifiers for Everyone Text-based safety classifiers are widely used for content moderation and increasingly to tune generative language model behavior - a topic of growing concern for the safety of digital assistants and chatbots. However, different policies require different classifiers, and safety policies themselves improve from iteration and adaptation. This paper intro.. 2023. 2. 15. [2023-02-14] 오늘의 자연어처리 Translating Natural Language to Planning Goals with Large-Language Models Recent large language models (LLMs) have demonstrated remarkable performance on a variety of natural language processing (NLP) tasks, leading to intense excitement about their applicability across various domains. Unfortunately, recent work has also shown that LLMs are unable to perform accurate reasoning nor solve plannin.. 2023. 2. 14. [2023-02-13] 오늘의 자연어처리 Robust Question Answering against Distribution Shifts with Test-Time Adaptation: An Empirical Study A deployed question answering (QA) model can easily fail when the test data has a distribution shift compared to the training data. Robustness tuning (RT) methods have been widely studied to enhance model robustness against distribution shifts before model deployment. However, can we improve a mod.. 2023. 2. 13. [2023-02-12] 오늘의 자연어처리 Sentiment analysis and opinion mining on educational data: A survey Sentiment analysis AKA opinion mining is one of the most widely used NLP applications to identify human intentions from their reviews. In the education sector, opinion mining is used to listen to student opinions and enhance their learning-teaching practices pedagogically. With advancements in sentiment annotation techniques and.. 2023. 2. 12. 이전 1 ··· 84 85 86 87 88 89 90 ··· 143 다음 반응형