Entity-conditioned input formatting substantially improves transformer performance on recipe ingredient detection and scientific process state tracking, but analysis shows the models exploit surface verb cues rather than forming deep entity representations.
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Effective Use of Transformer Networks for Entity Tracking
Entity-conditioned input formatting substantially improves transformer performance on recipe ingredient detection and scientific process state tracking, but analysis shows the models exploit surface verb cues rather than forming deep entity representations.