On the Noise Robustness of In-Context Learning for Text Generation
Large language models (LLMs) have shown impressive performance on downstream tasks
by in-context learning (ICL), which heavily relies on the quality of demonstrations selected …
by in-context learning (ICL), which heavily relies on the quality of demonstrations selected …
UniGen: Universal Domain Generalization for Sentiment Classification via Zero-shot Dataset Generation
Although pre-trained language models have exhibited great flexibility and versatility with
prompt-based few-shot learning, they suffer from the extensive parameter size and limited …
prompt-based few-shot learning, they suffer from the extensive parameter size and limited …
[PDF][PDF] Text Classification of German Mental Healthcare Data: A Hands-on Tutorial on Natural Language Processing Techniques.
S Hornstein, K Hilbert, D Ferizaj, K Zantvoort, U Lueken… - 2024 - osf.io
Abstract Natural Language Processing (NLP) is a promising approach for the extraction of
meaningful information from text data in clinical psychology. While ample resources cover …
meaningful information from text data in clinical psychology. While ample resources cover …