SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data

no code implementations • 6 Nov 2023 • Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister

Text-to-SQL aims to automate the process of generating SQL queries on a database from natural language text.

In-Context Learning Text-To-SQL

SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)

no code implementations • 26 May 2023 • Ruoxi Sun, Sercan Ö. Arik, Alex Muzio, Lesly Miculicich, Satya Gundabathula, Pengcheng Yin, Hanjun Dai, Hootan Nakhost, Rajarishi Sinha, Zifeng Wang, Tomas Pfister

Text-to-SQL, the process of translating natural language into Structured Query Language (SQL), represents a transformative application of large language models (LLMs), potentially revolutionizing how humans interact with data.

Data Augmentation In-Context Learning +3

Interpretable Sequence Learning for COVID-19 Forecasting

no code implementations • NeurIPS 2020 • Sercan O. Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister

We propose a novel approach that integrates machine learning into compartmental disease modeling to predict the progression of COVID-19.