Papers by Ankur Sikarwar

1 papers
When Can Transformers Ground and Compose: Insights from Compositional Generalization Benchmarks (2022.emnlp-main)

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Challenge: Recent benchmarks like ReaSCAN use navigation tasks grounded in a grid world to assess whether neural models exhibit compositional behaviour.
Approach: They propose a transformer-based model that outperforms specialized architectures on ReaSCAN and a modified version of gSCAN to test their performance.
Outcome: The proposed model outperforms specialized architectures on ReaSCAN and gSCAN on a grid world and can generalize to deeper input structures.

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