Search Results for author:
Found 3 papers, 3 papers with code
Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation
The robustness of Text-to-SQL parsers against adversarial perturbations plays a crucial role in delivering highly reliable applications.
LogiGAN: Learning Logical Reasoning via Adversarial Pre-training
We present LogiGAN, an unsupervised adversarial pre-training framework for improving logical reasoning abilities of language models.
Reasoning Like Program Executors
Reasoning over natural language is a long-standing goal for the research community.
Ranked #2 on
Question Answering
on DROP Test
(using extra training data)
Cannot find the paper you are looking for? You can
Submit a new open access paper.
