5 citations · 5 across the 6 of their papers we have counts for
6 papers
DIRECT: Decomposing Audience Preference and Creative Effect in Visual Content Analytics
Yizhi Liu, Balaji Padmanabhan, Siva Viswanathan
Which visual choices make a post perform better? A growing literature answers this question with pooled coefficients estimated across many creators, which platforms translate into…
Estimating Visual Attribute Effects in Advertising from Observational Data: A Deepfake-Informed Double Machine Learning Approach
Yizhi Liu, Balaji Padmanabhan, Siva Viswanathan
Digital advertising increasingly relies on visual content, yet marketers lack rigorous methods for understanding how specific visual attributes causally affect consumer engagement.…
What Exactly is a Deepfake?
Yizhi Liu, Balaji Padmanabhan, Siva Viswanathan
Deepfake technologies are often associated with deception, misinformation, and identity fraud, raising legitimate societal concerns. Yet such narratives may obscure a key insight:…
From Deception to Perception: The Surprising Benefits of Deepfakes for Detecting, Measuring, and Mitigating Bias
Yizhi Liu, Balaji Padmanabhan, Siva Viswanathan
While deepfake technologies have predominantly been criticized for potential misuse, our study demonstrates their significant potential as tools for detecting, measuring, and mitig…
Echoes of Biases: How Stigmatizing Language Affects AI Performance
Yizhi Liu, Weiguang Wang, Guodong Gordon Gao +1
Electronic health records (EHRs) serve as an essential data source for the envisioned artificial intelligence (AI)-driven transformation in healthcare. However, clinician biases re…
Automated PII Extraction from Social Media for Raising Privacy Awareness: A Deep Transfer Learning Approach
Yizhi Liu, Fang Yu Lin, Mohammadreza Ebrahimi +2
Internet users have been exposing an increasing amount of Personally Identifiable Information (PII) on social media. Such exposed PII can cause severe losses to the users, and info…