Papers by Maxime Petit
Dependency Parsing with Backtracking using Deep Reinforcement Learning (2022.tacl-1)
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| Challenge: | Greedy algorithms for NLP such as transition-based parsing are prone to error propagation. |
| Approach: | They propose to allow transition-based parsing to backtrack in cases where evidence contradicts the current solution. |
| Outcome: | The proposed behavior can be implemented on POS tagging and dependency parsing . it shows that backtracking is an effective means to fight error propagation . |