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Towards Continual Entity Learning in Language Models for Conversational Agents
[article]
2021
arXiv
pre-print
Neural language models (LM) trained on diverse corpora are known to work well on previously seen entities, however, updating these models with dynamically changing entities such as place names, song titles and shopping items requires re-training from scratch and collecting full sentences containing these entities. We aim to address this issue, by introducing entity-aware language models (EALM), where we integrate entity models trained on catalogues of entities into the pre-trained LMs. Our
arXiv:2108.00082v2
fatcat:zf4ojiq3v5gmnnbetk7r4crzbi