Coupling Distributed and Symbolic Execution for Natural Language QueriesDownload PDF

02 May 2025 (modified: 11 Mar 2017)ICLR 2017Readers: Everyone
Abstract: In this paper, we propose to combine neural execution and symbolic execution to query a table with natural languages. Our approach makes use the differentiability of neural networks and transfers (imperfect) knowledge to the symbolic executor before reinforcement learning. Experiments show our approach achieves high learning efficiency, high execution efficiency, high interpretability, as well as high performance.
TL;DR: ICLR 2017 workshop submission
Conflicts: pku.edu.cn, huawei.com, DeeplyCurious.ai
5 Replies

Loading

OpenReview is a long-term project to advance science through improved peer review with legal nonprofit status. We gratefully acknowledge the support of the OpenReview Sponsors. © 2025 OpenReview