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Update paper title for ALOE.

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David Ding
2021-08-04 17:13:40 +01:00
committed by Diego de Las Casas
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object_attention_for_reasoning/README.md
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@@ -1,16 +1,15 @@
Implementation of the object-based transformer model from
["Object-based attention for spatio-temporal reasoning"](https://arxiv.org/abs/2012.08508)
Implementation of the ALOE model
["Attention over learned object embeddings enables complex visual reasoning"](https://arxiv.org/abs/2012.08508)
[1].
This package includes source code for the transformer model,
This package includes source code for the ALOE transformer model,
pre-trained model parameters for the CLEVRER task,
and MONet [2] latent variables for all videos in the training
and validation sets. It does not include the model training code.
See Section 2 of [1] for details.
[1] David Ding, Felix Hill, Adam Santoro, Matt Botvinick. *Object-based
attention for spatio-temporal reasoning: Outperforming neuro-symbolic models
with flexible distributed architectures*.
[1] David Ding, Felix Hill, Adam Santoro, Malcolm Reynolds, Matt Botvinick.
*Attention over learned object embeddings enables complex visual reasoning*.
arXiv preprint arXiv:2012.08508, 2020.
[2] Chris P. Burgess, Loic Matthey, Nick Watters, Rishabh Kabra, Irina Higgins,
@@ -43,10 +42,9 @@ answers should be correct.
If you find the provided code useful, please cite this paper:
```
@article{objectattention2020,
title={Object-based attention for spatio-temporal reasoning: Outperforming
neuro-symbolic models with flexible distributed architectures},
author={David Ding and Felix Hill and Adam Santoro and Matt Botvinick},
@article{aloe2020,
title={Attention over learned object embeddings enables complex visual reasoning},
author={David Ding and Felix Hill and Adam Santoro and Malcolm Reynolds and Matt Botvinick},
journal={arXiv preprint arXiv:2012.08508},
year={2020}
}