Abstract
We restate the classical logical notion of generation/parsing reversibility in terms of feasible probabilistic sampling, and argue for an implementation based on finite-state factors. We propose a modular decomposition that reconciles generation accuracy with parsing robustness and allows the introduction of dynamic contextual factors. (Opinion Piece)
Cite
CITATION STYLE
Dymetman, M., Venkatapathy, S., & Xiao, C. (2015). Reversibility reconsidered: Finite-state factors for efficient probabilistic sampling in parsing and generation. In Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing (pp. 1990–1995). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d15-1233
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