3 papers
cs.LG2026
RAILS: Retrieval-Augmented Incremental LLM Clustering at Scale
Armin Oliya, Aleksandra Sawczuk, Radosław Białobrzeski
Using a Large Language Model (LLM) as the clusterer at production scale is hard: prompts cannot hold the entire label space, and per-document serial processing does not deliver the…
cs.CY2026
Sociodemographic Biases in Educational Counselling by Large Language Models
Tomasz Adamczyk, Wiktoria Mieleszczenko-Kowszewicz, Beata Bajcar +6
As Large Language Models (LLMs) are increasingly integrated into educational settings, understanding their potential biases is critical. This study examines sociodemographic biases…
cs.CL2026
How Annotation Trains Annotators: Competence Development in Social Influence Recognition
Maciej Markiewicz, Beata Bajcar, Wiktoria Mieleszczenko-Kowszewicz +8
Human data annotation, especially when involving experts, is often treated as an objective reference. However, many annotation tasks are inherently subjective, and annotators' judg…