Papers by Guillem Collell
Do Neural Network Cross-Modal Mappings Really Bridge Modalities? (P18-2)
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| Challenge: | Feed-forward networks are widely used in cross-modal applications to bridge modalities . success of such systems depends entirely on ability of mapping to make neighborhood structure akin to that of the target vectors. |
| Approach: | They propose to use a similarity measure to measure the neighborhood structure of neural network mappings. |
| Outcome: | The proposed model shows that the predicted neighborhood structure resembles more that of the input vectors than that of target vectors. |
Decoding Language Spatial Relations to 2D Spatial Arrangements (2020.findings-emnlp)
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| Challenge: | Using a model architecture, we decode text to 2D spatial arrangements in a multi-object and multi-relationship setting. |
| Approach: | They propose a model architecture Spatial-Reasoning Bert that decodes language to 2D spatial arrangements in a multi-object and multi-relationship setting. |
| Outcome: | The proposed model can generate complete abstract scenes if paired with a clip-arts predictor and can generalize to out-of-sample data to a reasonable extent. |