i-machine-think / am-i-compositionalLinks
☆62Updated 2 years ago
Alternatives and similar repositories for am-i-compositional
Users that are interested in am-i-compositional are comparing it to the libraries listed below
Sorting:
- Simple language-driven navigation tasks for studying compositional learning☆199Updated 5 years ago
- Paper: Learning to Recombine and Resample Data for Compositional Generalization☆10Updated 5 years ago
- This is a repository with the code for the EMNLP 2020 paper "Information-Theoretic Probing with Minimum Description Length"☆71Updated last year
- Annotated bibliographies.☆40Updated 6 years ago
- Grounded SCAN data set.☆70Updated 3 years ago
- Code for "Learning Compositional Rules via Neural Program Synthesis"☆60Updated 4 years ago
- ☆90Updated 3 years ago
- Diagnostic benchmark suite to explicitly test logical relational reasoning on natural language☆96Updated last year
- Code for the paper "Implicit Representations of Meaning in Neural Language Models"☆55Updated 2 years ago
- ☆11Updated 3 years ago
- ☆130Updated 2 years ago
- ☆62Updated 3 years ago
- Pragmatic models for generating and following instructions☆13Updated 5 years ago
- ☆38Updated last year
- Code for "Does syntax need to grow on trees? Sources of inductive bias in sequence to sequence networks"☆23Updated 5 years ago
- Pytorch implementation of the paper 'Compositional language emerge in a neural iterated learning' (ICLR 2020).☆15Updated 4 years ago
- Paper Reading in Neural Emergent Communication Literature☆30Updated 3 years ago
- Heuristic Analysis for NLI Systems☆126Updated 4 years ago
- Codebase describing experiments in Truncation Sampling as Language Model Desmoothing☆13Updated 2 years ago
- This code accompanies the paper "Information-Theoretic Probing for Linguistic Structure" published in ACL 2020.☆21Updated 5 years ago
- ☆22Updated 4 years ago
- Code and data for "A Systematic Assessment of Syntactic Generalization in Neural Language Models"☆29Updated 4 years ago
- Code accompanying our papers on the "Generative Distributional Control" framework☆118Updated 2 years ago
- ☆24Updated 4 years ago
- ☆22Updated 4 years ago
- [EMNLP 2020] Collective HumAn OpinionS on Natural Language Inference Data☆40Updated 3 years ago
- Implementation of "Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs"☆77Updated 4 years ago
- Learning the Difference that Makes a Difference with Counterfactually-Augmented Data☆169Updated 4 years ago
- A list of resources dedicated to compositionality☆14Updated 6 years ago
- ☆45Updated 4 years ago