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1. quantifier-rnn-learning quantifier-rnn-learning Public

   Accompanies the paper "Learnability and Semantic Universals" ; trains recurrent neural networks to learn to verify sentences with quantifiers in order to explain semantic universals

   Python 11 9

2. CLMBRs/ultk CLMBRs/ultk Public

   A library for research in unnatural language semantics

   Python 10 5

3. color-learning color-learning Public

   Accompanies the paper, "Ease of learning explains semantic universals". Generates and trains neural networks on artificial color systems, showing that _degree of convexity_ explains accuracy.

   Python 7 3

4. edugrad edugrad Public

   A minimal re-implementation of the PyTorch API (forward/backward autodifferentiation), intended for pedagogical uses

   Python 7

5. responsive-verbs responsive-verbs Public

   Accompanies the paper, "An Explanation of the Veridical Uniformity Universal"; trains neural networks to learn so-called responsive verbs in order to explain a semantic universal.

   Python 2 1

6. CLMBRs/modal-typology CLMBRs/modal-typology Public

   TeX 1 5