2020
ACL
ACL 2020
Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly
Abstract
AbstractBuilding on Petroni et al. 2019, we propose two new probing tasks analyzing factual knowledge stored in Pretrained Language Models (PLMs). (1) Negation. We find that PLMs do not distinguish between negated (‘‘Birds cannot [MASK]”) and non-negated (‘‘Birds can [MASK]”) cloze questions. (2) Mispriming. Inspired by priming methods in human psychology, we add “misprimes” to cloze questions (‘‘Talk? Birds can [MASK]”). We find that PLMs are easily distracted by misprimes. These results suggest that PLMs still have a long way to go to adequately learn human-like factual knowledge.
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Interdisciplinary Bridge
— Artificial Intelligence and Natural Language Processing
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Keyword Pioneer
— knowledge probing
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Cross-Pollinator
— Artificial Intelligence, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Machine Learning, Natural Language Processing, Reinforcement Learning, Speech & Audio
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Hot Topic Early Bird
— factual knowledge
Authors
Topics
Artificial Intelligence > Learning Paradigms > Transfer Learning
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Resources & Methods > Large Language Models
Artificial Intelligence > Core AI > Large Language Models
Natural Language Processing > Resources & Methods > Language Modeling