most citedWhat Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices

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cs.CL2026

Grokipedia vs Wikipedia: An LLM-Based Audit of Political Neutrality along Ideologies

Filippos Vlahos, Guillaume Bied, Tijl De Bie

Online encyclopedias shape political opinion and, through it, democratic discourse. In late 2025, Grokipedia was released, an encyclopedia written entirely by the LLM Grok. One mot…

cs.CL2026

STEP: Career-Path Recommendation via Temporal and Educational Trajectory Modeling

Iman Johary, Guillaume Bied, Alexandru C. Mara +1

Career paths encode decades of skill acquisition, role transitions, and educational investment, and understanding them at scale underpins workforce planning, labor market policy, a…

cs.CL2026

JobHop v2: A Large-Scale Career Trajectory Dataset from Unstructured Resumes

Iman Johary, Guillaume Bied, Alexandru C. Mara +1

Large-scale, richly annotated career trajectory data underpins workforce planning, job recommendation, and labour market analysis, yet publicly available datasets are either small,…

cs.CL2026

Cards Against LLMs: Benchmarking Humor Alignment in Large Language Models

Yousra Fettach, Guillaume Bied, Hannu Toivonen +1

Humor is one of the most culturally embedded and socially significant dimensions of human communication, yet it remains largely unexplored as a dimension of Large Language Model (L…

cs.CL2025★ 1 cited

What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices

Sander Noels, Guillaume Bied, Maarten Buyl +4

Large Language Models (LLMs) are increasingly deployed as gateways to information, yet their content moderation practices remain underexplored. This work investigates the extent to…