29 citations · 30 across the 4 of their papers we have counts for
7 papers · 1 filter
Towards Scalable Schema Mapping using Large Language Models
Christopher Buss, Mahdis Safari, Arash Termehchy +2
The growing need to integrate information from a large number of diverse sources poses significant scalability challenges for data integration systems. These systems often rely on…
Towards Consistent Language Models Using Declarative Constraints
Jasmin Mousavi, Arash Termehchy
Large language models have shown unprecedented abilities in generating linguistically coherent and syntactically correct natural language output. However, they often return incorre…
Multi-Agent Join
Vahid Ghadakchi, Mian Xie, Arash Termehchy +4
It is crucial to provide real-time performance in many applications, such as interactive and exploratory data analysis. In these settings, users often need to view subsets of query…
A Survey on Data Cleaning Methods for Improved Machine Learning Model Performance
Ga Young Lee, Lubna Alzamil, Bakhtiyar Doskenov +1
Data cleaning is the initial stage of any machine learning project and is one of the most critical processes in data analysis. It is a critical step in ensuring that the dataset is…
Learning Over Dirty Data Without Cleaning
Jose Picado, John Davis, Arash Termehchy +1
Real-world datasets are dirty and contain many errors. Examples of these issues are violations of integrity constraints, duplicates, and inconsistencies in representing data values…
Managing Variability in Relational Databases by VDBMS
Parisa Ataei, Qiaoran Li, Eric Walkingshaw +1
Variability inherently exists in databases in various contexts which creates database variants. For example, variants of a database could have different schemas/content (database e…