Published November 22, 2024
| Version 1
Dataset
Open
Deep neural networks and humans both benefit from compositional language structure
Authors/Creators
-
1.
University of Southern Denmark
-
2.
Max Planck Institute for Psycholinguistics
- 3. Tel Aviv University
- 4. University of Glasgow
Description
This dataset holds the results generated in the paper:
Deep neural networks and humans both benefit from compositional language structure
by L. Galke, Y. Ram, and L. Raviv.
Files
README.md
Files
(196.8 MB)
| Name | Size | Download all |
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md5:5a1fed32e34554356f68e637238d75b1
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11.1 kB | Preview Download |
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md5:2ed1863fde3fbd6ef48c55505a195e22
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13.6 kB | Preview Download |
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md5:32c7d524b99844b82a2153c5c7d599d4
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7.1 kB | Preview Download |
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md5:4196def86ef8a601f2775fa5abd0ca17
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1.4 kB | Preview Download |
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md5:6ff1e96ecccf8bacdf75993ce0606b7c
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129.8 MB | Preview Download |
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md5:bce32fac99caed9f1f5ca30506b44621
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67.0 MB | Preview Download |
Additional details
Related works
- Is supplement to
- Preprint: arXiv:2302.12239 (arXiv)
Software
- Repository URL
- https://github.com/lgalke/easy2deeplearn