Sample stimuli










How to use
from brainscore_language import load_benchmark benchmark = load_benchmark("syntaxgym-subordination_pp-pp") score = benchmark(my_model)
Model scores
Min Alignment
Max Alignment
Rank |
Model |
Score |
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1 |
X
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2 |
X
|
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3 |
X
|
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4 |
X
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5 |
X
|
|
6 |
X
|
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7 |
X
|
|
8 |
X
|
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9 |
X
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10 |
X
|
|
11 |
X
|
|
12 |
X
|
|
13 |
X
|
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14 |
X
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Benchmark bibtex
@inproceedings{gauthier-etal-2020-syntaxgym, title = "{S}yntax{G}ym: An Online Platform for Targeted Evaluation of Language Models", author = "Gauthier, Jon and Hu, Jennifer and Wilcox, Ethan and Qian, Peng and Levy, Roger", booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations", month = jul, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.acl-demos.10", pages = "70--76", abstract = "Targeted syntactic evaluations have yielded insights into the generalizations learned by neural network language models. However, this line of research requires an uncommon confluence of skills: both the theoretical knowledge needed to design controlled psycholinguistic experiments, and the technical proficiency needed to train and deploy large-scale language models. We present SyntaxGym, an online platform designed to make targeted evaluations accessible to both experts in NLP and linguistics, reproducible across computing environments, and standardized following the norms of psycholinguistic experimental design. This paper releases two tools of independent value for the computational linguistics community: 1. A website, syntaxgym.org, which centralizes the process of targeted syntactic evaluation and provides easy tools for analysis and visualization; 2. Two command-line tools, {`}syntaxgym{`} and {`}lm-zoo{`}, which allow any user to reproduce targeted syntactic evaluations and general language model inference on their own machine.", }
Ceiling
1.00.Note that scores are relative to this ceiling.
Data: syntaxgym-subordination_pp
Metric: pp