Papers with COGS dataset
Compositional generalization with a broad-coverage semantic parser (2022.starsem-1)
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| Challenge: | Recent work has shown that compositional generalization on COGS is difficult and complex. |
| Approach: | They propose a compositional semantic parser that solves compositional generalization on COGS dataset. |
| Outcome: | The AM parser solves compositional generalization on the COGS dataset. |
Structural generalization in COGS: Supertagging is (almost) all you need (2023.emnlp-main)
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| Challenge: | Recent studies have shown that neural networks fail to generalize on out-of-distribution examples. |
| Approach: | They extend a neural graph-based parsing framework to address compositional generalization limitations . they introduce a supertagging step with valency constraints and reduce the graph prediction problem . |
| Outcome: | The proposed approach improves results on COGS datasets that require structural generalization. |