4 citations · 5 across the 14 of their papers we have counts for
16 papers
Do Third-Party Web Traffic Estimates Preserve Causal Variation?
Mehrzad Khosravi, Hema Yoganarasimhan
Researchers increasingly rely on third-party platforms such as Similarweb and Semrush to measure web traffic when first-party analytics are unavailable. Yet these platforms report…
Adaptive Ad Load Design for Sponsored Search Markets: Evidence, Theory, and Deployment
Mohammad Rashid, Hema Yoganarasimhan
Ad-load design is a central supply-side decision in sponsored search: more sponsored slots can raise revenue, but may crowd out organic results and degrade user outcomes. We study…
Boundedly Rational Meta-Learning in Sequential Consumer Choice
Mehrzad Khosravi, Max Kleiman-Weiner, Hema Yoganarasimhan
Many consumer decisions involve repeated choices under uncertainty, where experience in one context may inform decisions in another. For example, experience with a brand in one mar…
Rectification Difficulty and Optimal Sample Allocation in LLM-Augmented Surveys
Zikun Ye, Hema Yoganarasimhan
Large Language Models can generate synthetic survey responses at low cost, but their accuracy varies unpredictably across questions. We study the design problem of allocating a fix…
Impact of AI Search Summaries on Website Traffic: Evidence from Google AI Overviews and Wikipedia
Mehrzad Khosravi, Hema Yoganarasimhan
Search engines increasingly display AI-generated answers above organic links, potentially displacing traffic to upstream publishers. We estimate the impact of Google's AI Overviews…
TextBO: Bayesian Optimization in Language Space for Eval-Efficient Self-Improving AI
Enoch Hyunwook Kang, Hema Yoganarasimhan
Large Language Models (LLMs) have enabled self-improving AI systems that iteratively generate, evaluate, and refine their outcomes. Recent studies show that prompt-optimization-bas…
Channel Adoption Pathways and Post-Adoption Behavior
Shirsho Biswas, Hema Yoganarasimhan, Haonan Zhang
The rapid growth of digital shopping channels has led many traditional retailers to invest in e-commerce websites and mobile apps. While prior research shows that multichannel cust…
How does online shopping affect offline price sensitivity?
Shirsho Biswas, Hema Yoganarasimhan, Haonan Zhang
The rapid rise of e-commerce has transformed consumer behavior, prompting questions about how online adoption influences offline shopping. We examine whether consumers who adopt a…
Fair Document Valuation in LLM Summaries via Shapley Values
Zikun Ye, Hema Yoganarasimhan
Large Language Models (LLMs) increasingly power search engines and AI assistants that retrieve and summarize content from many sources. By serving answers directly, these systems o…
Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs
Mengjie Cheng, Elie Ofek, Hema Yoganarasimhan
We study how media firms can use LLMs to generate news content that aligns with multiple objectives -- making content more engaging while maintaining a preferred level of polarizat…
Visual Polarization Measurement Using Counterfactual Image Generation
Mohammad Mosaffa, Omid Rafieian, Hema Yoganarasimhan
Political polarization is a significant issue in American politics, influencing public discourse, policy, and consumer behavior. While studies on polarization in news media have ex…
An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model
Enoch H. Kang, Hema Yoganarasimhan, Lalit Jain
We study the problem of estimating Dynamic Discrete Choice (DDC) models, also known as offline Maximum Entropy-Regularized Inverse Reinforcement Learning (offline MaxEnt-IRL) in ma…
LOLA: LLM-Assisted Online Learning Algorithm for Content Experiments
Zikun Ye, Hema Yoganarasimhan, Yufeng Zheng
Modern media firms require automated and efficient methods to identify content that is most engaging and appealing to users. Leveraging a large-scale dataset from Upworthy (a news…
Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets
Amandeep Singh, Ye Liu, Hema Yoganarasimhan
Choice modeling is at the core of understanding how changes to the competitive landscape affect consumer choices and reshape market equilibria. In this paper, we propose a fundamen…
A Recursive Partitioning Approach for Dynamic Discrete Choice Modeling in High Dimensional Settings
Ebrahim Barzegary, Hema Yoganarasimhan
Dynamic discrete choice models are widely employed to answer substantive and policy questions in settings where individuals' current choices have future implications. However, esti…
Design and Evaluation of Personalized Free Trials
Hema Yoganarasimhan, Ebrahim Barzegary, Abhishek Pani
Free trial promotions, where users are given a limited time to try the product for free, are a commonly used customer acquisition strategy in the Software as a Service (SaaS) indus…