Factual probe
3 papers with code • 3 benchmarks • 2 datasets
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Most implemented papers
BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models
We release the BEAR datasets and an open-source framework that implements the probing approach to the research community to facilitate the evaluation and development of LMs.
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation
We cast a suite of information extraction tasks into a text-to-triple translation framework.
DeepStruct: Pretraining of Language Models for Structure Prediction
We introduce a method for improving the structural understanding abilities of language models.