707 citations · 1.3k across the 5 of their papers we have counts for
5 papers
Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows
Piotr Miłkowski, Konrad Karanowski, Patryk Wielopolski +3
Designing predictive models for subjective problems in natural language processing (NLP) remains challenging. This is mainly due to its non-deterministic nature and different perce…
From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment Analysis
Stanisław Woźniak, Jan Kocoń
In the era of artificial intelligence, data is gold but costly to annotate. The paper demonstrates a groundbreaking solution to this dilemma using ChatGPT for text augmentation in…
Deep Emotions Across Languages: A Novel Approach for Sentiment Propagation in Multilingual WordNets
Jan Kocoń
Sentiment analysis involves using WordNets enriched with emotional metadata, which are valuable resources. However, manual annotation is time-consuming and expensive, resulting in…
ChatGPT: Jack of all trades, master of none
Jan Kocoń, Igor Cichecki, Oliwier Kaszyca +17
OpenAI has released the Chat Generative Pre-trained Transformer (ChatGPT) and revolutionized the approach in artificial intelligence to human-model interaction. Several publication…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…