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20232026
most citedOn Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model

10 citations · 17 across the 17 of their papers we have counts for

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9 papers · 1 filter

cs.AI2026

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…

cs.AI2026

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…

cs.CL2026

WildSEEK: Evaluating Language Models for Information-Seeking

Tanise Ceron, Joachim Baumann, Elisa Bassignana +3

Language models are increasingly mediating information access to end users, urging a systematic evaluation of their responses for a fair and reliable information ecosystem. Existin…

cs.CL2026

Humanly: A Configurable and Traceable Environment for Human-AI Collaborative Writing

Shenzhe Zhu, Haoqian Zhang, Xu Yang +7

Teachers, conference chairs, and public readers all judge writing from limited evidence, seeing only a finished document and not the process that produced it. Final text alone cann…

cs.CL2026

Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability

Alicia Parrish, Rajat Shinde, Sanket Badhe +57

Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional laws, socio-linguistic nuances,…

cs.CR2026

SecureForge: Finding and Preventing Vulnerabilities in LLM-Generated Code via Prompt Optimization

Houjun Liu, Lisa Einstein, John Yang +5

LLM coding agents now generate code at an unprecedented scale, yet LLM-generated code introduces cybersecurity vulnerabilities into codebases without human involvement. Even when f…

cs.AI2026

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…

cs.AI2026

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,…

cs.IR2026

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…