Papers with probe language models

1 papers
Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and Recognition (2022.lrec-1)

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Challenge: Existing studies have focused on auto-regressive models for generalization in named entity (NE) typing (NET) and recognition (NER) . however, little has been done in this direction for auto-Regressive LMs despite their popularity and potential to express a wide variety of NLP tasks in the same unified format.
Approach: They propose to probe auto-regressive LMs for NET and NER generalization by resorting to meta-learning to assess the model's memorization of NEs.
Outcome: The proposed model performs well on NET and NER generalization tasks, while relying more on NE than contextual cues in few-shot NER.

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