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Data · dataset · 2022

NumerSense

Listed in Hugging Face Datasets

NumerSense is a new numerical commonsense reasoning probing task, with a diagnostic dataset consisting of 3,145 masked-word-prediction probes.

Description

We propose to study whether numerical commonsense knowledge can be induced from pre-trained language models like BERT, and to what extent this access to knowledge robust against adversarial examples is. We hope this will be beneficial for tasks such as knowledge base completion and open-domain question answering.

Links

Where it is published

Documentation and papers

Catalogue records · 1

Topics

Stated by source
fill mask · text generation
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
Hugging Face DatasetsINK-USC/numer_sense15 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:fill-masksource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
concepts[task].hf_task:text-generationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
licensesource · Hugging Faceconnector:huggingface@1.0.0/tags[license:*]
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0