2 citations · 4 across the 10 of their papers we have counts for
10 papers
Causal Explanations for Disparate Trends: Where and Why?
Tal Blau, Brit Youngmann, Anna Fariha +1
During data analysis, we are often perplexed by certain disparities observed between two groups of interest within a dataset. To better understand an observed disparity, we need ex…
Silenced Biases: The Dark Side LLMs Learned to Refuse
Rom Himelstein, Amit LeVi, Brit Youngmann +2
Safety-aligned large language models (LLMs) are becoming increasingly widespread, especially in sensitive applications where fairness is essential and biased outputs can cause sign…
Fair and Actionable Causal Prescription Ruleset
Benton Li, Nativ Levy, Brit Youngmann +2
Prescriptions, or actionable recommendations, are commonly generated across various fields to influence key outcomes such as improving public health, enhancing economic policies, o…
Summarized Causal Explanations For Aggregate Views (Full version)
Brit Youngmann, Michael Cafarella, Amir Gilad +1
SQL queries with group-by and average are frequently used and plotted as bar charts in several data analysis applications. Understanding the reasons behind the results in such an a…
Finding Convincing Views to Endorse a Claim
Shunit Agmon, Amir Gilad, Brit Youngmann +2
Recent studies investigated the challenge of assessing the strength of a given claim extracted from a dataset, particularly the claim's potential of being misleading and cherry-pic…
Causal Data Integration
Brit Youngmann, Michael Cafarella, Babak Salimi +1
Causal inference is fundamental to empirical scientific discoveries in natural and social sciences; however, in the process of conducting causal inference, data management problems…
On Explaining Confounding Bias
Brit Youngmann, Michael Cafarella, Yuval Moskovitch +1
When analyzing large datasets, analysts are often interested in the explanations for surprising or unexpected results produced by their queries. In this work, we focus on aggregate…
Guided Exploration of Data Summaries
Brit Youngmann, Sihem Amer-Yahia, Aurélien Personnaz
Data summarization is the process of producing interpretable and representative subsets of an input dataset. It is usually performed following a one-shot process with the purpose o…
Algorithmic Copywriting: Automated Generation of Health-Related Advertisements to Improve their Performance
Brit Youngmann, Ran Gilad-Bachrach, Danny Karmon +1
Search advertising, a popular method for online marketing, has been employed to improve health by eliciting positive behavioral change. However, writing effective advertisements re…
Detecting Parkinson's Disease from interactions with a search engine: Is expert knowledge sufficient?
Liron Allerhand, Brit Youngmann, Elad Yom-Tov +1
Parkinson's disease (PD) is a slowly progressing neurodegenerative disease with early manifestation of motor signs. Recently, there has been a growing interest in developing automa…