10 citations · 17 across the 17 of their papers we have counts for
5 papers · 1 filter
Prompt Revision as a Source of Cultural Bias in Text-to-Image Systems
Aleksandra Urman, Elsa Lichtenegger, Salima Jaoua +7
Commercial text-to-image systems silently revise user prompts before generating images, a step users typically cannot disable or even see. Yet, existing audits of cultural bias exa…
API Benchmark Scores Do Not Reliably Transfer to Chatbot Interfaces
Jennifer Wang, Joachim Baumann, Daniel E. Ho +1
Benchmark scores are a central currency in model releases: they inform purchasing decisions, shape public trust, and influence policy. Yet, a key assumption underlying benchmark sc…
Stop Automating Peer Review Without Rigorous Evaluation
Joachim Baumann, Jiaxin Pei, Sanmi Koyejo +1
Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used to produce paper reviews. W…
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,…
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…