Papers with entity tracking approaches

1 papers
Entity Tracking via Effective Use of Multi-Task Learning Model and Mention-guided Decoding (2023.eacl-main)

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Challenge: State-of-the-art entity tracking approaches either design complicated model architectures or rely on task-specific pre-training to achieve good results.
Approach: They propose a multi-task learning-enabled entity tracking approach that utilizes knowledge gained from general domain tasks to improve entity tracking.
Outcome: The proposed approach achieves state-of-the-art on two popular entity tracking datasets, even though it does not require any task-specific architecture design or pre-training.

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