3 citations · 5 across the 12 of their papers we have counts for
3 papers · 1 filter
From Generalized Laughter to Personalized Chuckles: Unleashing the Power of Data Fusion in Subjective Humor Detection
Julita Bielaniewicz, Przemysław Kazienko
The vast area of subjectivity in Natural Language Processing (NLP) poses a challenge to the solutions typically used in generalized tasks. As exploration in the scope of generalize…
Towards Model-Based Data Acquisition for Subjective Multi-Task NLP Problems
Kamil Kanclerz, Julita Bielaniewicz, Marcin Gruza +3
Data annotated by humans is a source of knowledge by describing the peculiarities of the problem and therefore fueling the decision process of the trained model. Unfortunately, the…
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…