collaborators

5 papers

cs.HC2026

MIVAIS: A Study Environment for Multi-Agent Mixed-Initiative Visual Analytics Applications

Tobias Stähle, Simon Schneider, Rita Sevastjanova +1

Mixed-initiative Visual Analytics (VA) systems empower human users by interleaving human intuition with software agents and their machine intelligence. However, the development and…

cs.IR2026

GuidedRAG: Semantic Steering of Retrieval-Augmented Generation

Matthijs Jansen op de Haar, Tobias Stähle, Lorenzo Gatti

In this work, we propose GuidedRAG, a novel extension to traditional Retrieval-Augmented Generation (RAG) that introduces a dedicated selection stage and semantic steering during r…

cs.HC2026

From Interaction to Intent: Inferring User Objectives from Provenance Logs

Steffen Holter, Tobias Stähle, Arpit Narechania +1

The ability to automatically infer analytic intent from user interaction histories could enable interactive AI systems to proactively assist users during exploratory data analysis.…

cs.IR2026

All Relations Lead to Rome: Automated Knowledge Graph Creation and Question Generation

Matthijs Jansen op de Haar, Tobias Stähle, Lorenzo Gatti

Large language models have substantially improved information retrieval and question answering; however, existing datasets generally support either vector-based retrieval over unst…

cs.HC2026

VACP: Visual Analytics Context Protocol

Tobias Stähle, Péter Ferenc Gyarmati, Thilo Spinner +3

The rise of AI agents introduces a fundamental shift in Visual Analytics (VA), in which agents act as a new user group. Current agentic approaches - based on computer vision and ra…