ServiceNow Research

Torsten Scholak

Torsten Scholak

Research Scientist

Human Machine Interaction Through Language

Torsten is an Applied Research Scientist and project leader in the Human-Machine Interaction Through Language program at ServiceNow Research. His current research interest is deep learning for code, especially with large language models and integrating symbolic reasoning. In 2022, he is co-organizing the Deep Learning for Code workshop at ICLR. Previously, he has been more focused on semantic parsing. He has published several papers on translating natural language questions into SQL queries. One of his most successful works on this topic is the PICARD project, which is a state-of-the-art text-to-SQL parser.

  • Large Language Models
  • Text2Code


Towards Neural Functional Program Evaluation. Conference on Neural Information Processing Systems (NeurIPS),  2021.

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DuoRAT: Towards Simpler Text-to-SQL Models. North American Chapter of the Association for Computational Linguistics (NAACL),  2021.

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