Papers by Alban Petit
On Graph-based Reentrancy-free Semantic Parsing (2023.tacl-1)
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| Challenge: | Existing graph-based approaches for semantic parsing fail on compositional generalization tasks. |
| Approach: | They propose a graph-based approach for semantic parsing that solves two problems . they propose two algorithms based on constraint smoothing and conditional gradient to approximate these problems. |
| Outcome: | The proposed graph-based approach delivers state-of-the-art results on GeoQuery, Scan, and Clevr . |
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. |