Learning representations of entity mentions is a core component of modern entity linking systems for both candidate generation and making linking predictions.
Ranked #1 on Entity Linking on ZESHEL
Personality computing and affective computing have gained recent interest in many research areas.
Multimodal Deep Learning has garnered much interest, and transformers have triggered novel approaches, thanks to the cross-attention mechanism.
Previous work has shown promising results in performing entity linking by measuring not only the affinities between mentions and entities but also those amongst mentions.
We propose a new deep learning model for goal-driven tasks that require intuitive physical reasoning and intervention in the scene to achieve a desired end goal.