2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.DB2024★ 2 cited
SHARQ: Explainability Framework for Association Rules on Relational Data
Hadar Ben-Efraim, Susan B. Davidson, Amit Somech
Association rules are an important technique for gaining insights over large relational datasets consisting of tuples of elements (i.e. attribute-value pairs). However, it is diffi…
cs.CL2024★ 1 cited
Generating Tables from the Parametric Knowledge of Language Models
Yevgeni Berkovitch, Oren Glickman, Amit Somech +1
We explore generating factual and accurate tables from the parametric knowledge of large language models (LLMs). While LLMs have demonstrated impressive capabilities in recreating…
cs.DB2024
LINX: A Language Driven Generative System for Goal-Oriented Automated Data Exploration
Tavor Lipman, Tova Milo, Amit Somech +2
Data exploration is a challenging process in which users examine a dataset by iteratively employing a series of queries. While in some cases the user explores a new dataset to beco…