4 citations · 4 across the 4 of their papers we have counts for
7 papers
SWE-chat: Coding Agent Interactions From Real Users in the Wild
Joachim Baumann, Vishakh Padmakumar, Xiang Li +3
AI coding agents are being adopted at scale, yet we lack empirical evidence on how people actually use them and how much of their output is useful in practice. We present SWE-chat,…
GoogleTrendArchive: A Year-Long Archive of Real-Time Web Search Trends Worldwide
Aleksandra Urman, Anikó Hannák, Joachim Baumann
GoogleTrendArchive is a comprehensive archive of Google Trending Now data spanning over one year (from November 28, 2024 to January 3, 2026) across 125 countries and 1,358 location…
Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy
Desheng Hu, Joachim Baumann, Aleksandra Urman +4
Google Search increasingly surfaces AI-generated content through features like AI Overviews (AIO) and Featured Snippets (FS), which users frequently rely on despite having no contr…
Reduced AI Acceptance After the Generative AI Boom: Evidence From a Two-Wave Survey Study
Joachim Baumann, Aleksandra Urman, Ulrich Leicht-Deobald +3
The rapid adoption of generative artificial intelligence (GenAI) technologies has led many organizations to integrate AI into their products and services, often without considering…
Large Language Model Hacking: Quantifying the Hidden Risks of Using LLMs for Text Annotation
Joachim Baumann, Paul Röttger, Aleksandra Urman +4
Large language models are rapidly transforming social science research by enabling the automation of labor-intensive tasks like data annotation and text analysis. However, LLM outp…
SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors
Tiancheng Hu, Joachim Baumann, Lorenzo Lupo +3
Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only if they faithfully reflect real human b…