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Attentive Guidance

This repository contains the implementation of Attentive Guidance, a technique that demonstrates that vanilla seq2seq models with attention can achieve compositional solutions without the need to explicitly build this into their architecture 1.

The repositary builds on top of the seq2seq library machine and adds to this library an attention loss and data field. The file train_model.py is based on the example training script provided in machine, but adds command line arguments to facilitate training a model with attention loss. The file test.sh contains several (toy) examples of how to invoke these parameters, for a complete overview, use the help function of the train_model.py script.

[1] Hupkes D., Singh A.K., Korrel K., Kruszewski G. and, Bruni E. (2018) Learning compositionally through attentive guidance.

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