3 citations · 3 across the 3 of their papers we have counts for
3 papers
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners
Kezhi Kong, Jiani Zhang, Zhengyuan Shen +5
Large Language Models (LLMs) trained on large volumes of data excel at various natural language tasks, but they cannot handle tasks requiring knowledge that has not been trained on…
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection
Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen +4
Large Language Models (LLMs) can adapt to new tasks via in-context learning (ICL). ICL is efficient as it does not require any parameter updates to the trained LLM, but only few an…
NameGuess: Column Name Expansion for Tabular Data
Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan +3
Recent advances in large language models have revolutionized many sectors, including the database industry. One common challenge when dealing with large volumes of tabular data is…