Data · dataset · 2022
ReClor
Listed in Hugging Face Datasets
Logical reasoning is an important ability to examine, analyze, and critically evaluate arguments as they occur in ordinary language as the definition from LSAC.
Description
ReClor is a dataset extracted from logical reasoning questions of standardized graduate admission examinations. Empirical results show that the state-of-the-art models struggle on ReClor with poor performance indicating more research is needed to essentially enhance the logical reasoning ability of current models.
We hope this dataset could help push Machine Reading Comprehension (MRC) towards more complicated reasonin
Links
Where it is published
- Hugging Face dataset page huggingface.co/datasets/community-datasets/reclor ↗
landing page · from Hugging Face
Catalogue records · 1
- Hub API huggingface.co/api/datasets/community-datasets/reclor ↗
metadata API · from Hugging Face
Topics
- From keywords
- Computer Science & AI
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Hugging Face Datasets | community-datasets/reclor | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · Hugging Face | connector:huggingface@1.0.0 | /gated |
| concepts[field].local:field:computer-science-ai | mapping · Hugging Face | connector:huggingface@1.0.0 | |
| created_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| description | source · Hugging Face | connector:huggingface@1.0.0 | /description |
| publication_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| title | source · Hugging Face | connector:huggingface@1.0.0 | /id |
| updated_date | source · Hugging Face | connector:huggingface@1.0.0 |