Fine-tuning and Sampling Strategies for Multimodal Role Labeling of Entities under Class Imbalance
We propose our solution to the multimodal semantic role labeling task from the CONSTRAINT’22 workshop. The task aims at classifying entities in memes into classes such as “hero” and “villain”. We use several pre-trained multi-modal models to jointly encode the text and image of the memes, and implement three systems to classify the role of the entities. We propose dynamic sampling strategies to tackle the issue of class imbalance. Finally, we perform qualitative analysis on the representations of the entities.
PDF AbstractTasks
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
