In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

We use Waseem and Hovy BIBREF5, Davidson et al. BIBREF9, and Waseem et al. BIBREF10 as baselines and compare the results with our different fine-tuning strategies using pre-trained BERTbase model.
Question: What existing approaches do they compare to?
Waseem and Hovy BIBREF5, Davidson et al. BIBREF9, and Waseem et al. BIBREF10

Our submissions ranked second (EI-Reg), second (EI-Oc), fourth (V-Reg) and fifth (V-Oc), demonstrating that the proposed method is accurate in automatically determining the intensity of emotions and sentiment of Spanish tweets.
Question: What subtasks did they participate in?
Answer with content missing: (Subscript 1: "We did not participate in subtask 5 (E-c)") Authors participated in EI-Reg, EI-Oc, V-Reg and V-Oc subtasks.

Differently to textual data, our goal in this paper is to explore the large amount of categorical data that is often collected in travel surveys. This includes trip purpose, education level, or family type. We also consider other variables that are not necessarily of categorical nature, but typically end up as dummy encoding, due to segmentation, such as age, income, or even origin/destination pair.
Question: How do they model travel behavior?
The data from collected travel surveys is used to model travel behavior.