29 citations · 62 across the 20 of their papers we have counts for
6 papers · 1 filter
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data
Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha +4
Text-to-SQL aims to automate the process of generating SQL queries on a database from natural language text. In this work, we propose "SQLPrompt", tailored to improve the few-shot…
Effective Large Language Model Adaptation for Improved Grounding and Citation Generation
Xi Ye, Ruoxi Sun, Sercan Ö. Arik +1
Large language models (LLMs) have achieved remarkable advancements in natural language understanding and generation. However, one major issue towards their widespread deployment in…
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)
Ruoxi Sun, Sercan Ö. Arik, Alex Muzio +8
Text-to-SQL, the process of translating natural language into Structured Query Language (SQL), represents a transformative application of large language models (LLMs), potentially…
Better Zero-Shot Reasoning with Self-Adaptive Prompting
Xingchen Wan, Ruoxi Sun, Hanjun Dai +2
Modern large language models (LLMs) have demonstrated impressive capabilities at sophisticated tasks, often through step-by-step reasoning similar to humans. This is made possible…
Universal Self-Adaptive Prompting
Xingchen Wan, Ruoxi Sun, Hootan Nakhost +4
A hallmark of modern large language models (LLMs) is their impressive general zero-shot and few-shot abilities, often elicited through in-context learning (ICL) via prompting. Howe…
Neural Spline Search for Quantile Probabilistic Modeling
Ruoxi Sun, Chun-Liang Li, Sercan O. Arik +3
Accurate estimation of output quantiles is crucial in many use cases, where it is desired to model the range of possibility. Modeling target distribution at arbitrary quantile leve…