3 papers
cs.IR2026
From Skill Extraction to Multistakeholder Recommendation: A Two-Stage Framework for Bias Governance in Skills-Based Job Matching
Andrea Forster, Gregor Autischer, Dominik Kowald +1
AI-based labor-market systems or platforms can affect access to job opportunities prior to organizational candidate rankings or hiring decisions. Such applications warrant caution,…
cs.IR2026
Fair Agents: Balancing Multistakeholder Alignment in Multi-Agent Personalization Systems
Andrea Forster, Peter Müllner, Denis Helic +2
LLM agents are increasingly used for personalization due to their ability to communicate directly with users in natural language, integrate external knowledge bases, and negotiate…
cs.IR2025
Exploring the Effect of Context-Awareness and Popularity Calibration on Popularity Bias in POI Recommendations
Andrea Forster, Simone Kopeinik, Denic Helic +2
Point-of-interest (POI) recommender systems help users discover relevant locations, but their effectiveness is often compromised by popularity bias, which disadvantages less popula…