collaborators

6 papers

cs.CL2026

No PUN Intended: Plausible Unknown Names for Person-Centred LLM Evaluation

Dimitri Staufer, David Hartmann, Ibrahim Baroud

Person names are widely used as prompt variables in LLM evaluations of factuality, privacy leakage, bias and abstention, but when a name's evidential status is uncontrolled, measur…

cs.CL2026

Bye Bye Perspective API: Lessons for Measurement Infrastructure in NLP, CSS and LLM Evaluation

David Hartmann, Manuel Tonneau, Angelie Kraft +7

The closure of Perspective API at the end of 2026 discards what has functioned as the de facto standard for automated toxicity measurement in NLP, CSS, and LLM evaluation research.…

cs.HC2026

Human-Centred LLM Privacy Audits: Findings and Frictions

Dimitri Staufer, Kirsten Morehouse, David Hartmann +1

Large language models (LLMs) learn statistical associations from massive training corpora and user interactions, and deployed systems can surface or infer information about individ…

cs.HC2026

What Do LLMs Associate with Your Name? A Human-Centered Black-Box Audit of Personal Data

Dimitri Staufer, Kirsten Morehouse

Large language models (LLMs), and conversational agents based on them, are exposed to personal data (PD) during pre-training and during user interactions. Prior work shows that PD…

cs.CL2025

What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests

Dimitri Staufer

Large Language Models (LLMs) can memorize and reveal personal information, raising concerns regarding compliance with the EU's GDPR, particularly the Right to Be Forgotten (RTBF).…

cs.HC2025

Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variations

David Hartmann, Amin Oueslati, Dimitri Staufer +3

Commercial content moderation APIs are marketed as scalable solutions to combat online hate speech. However, the reliance on these APIs risks both silencing legitimate speech, call…