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publications
A New Approach on Estimating Germany’s Mobile Broadband Coverage based on Crowdsourced Data
Published in Mobile Communication-Technologies and Applications; 27th ITG-Symposium, 2023
A novel approach for estimating mobile broadband coverage in Germany using crowdsourced data, presented at the 27th ITG-Symposium on Mobile Communication.
Recommended citation: Wolff, C., Tessmer, A., & Aschenbruck, N. (2023). "A New Approach on Estimating Germany's Mobile Broadband Coverage based on Crowdsourced Data." Mobile Communication-Technologies and Applications; 27th ITG-Symposium, 31-36.
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A Review of Nine Physics Engines for Reinforcement Learning Research
Published in arXiv preprint arXiv:2407.08590, 2024
A comprehensive review of nine physics engines for reinforcement learning research, analyzing their capabilities and suitability for RL applications.
Recommended citation: Kaup, M., Wolff, C., Hwang, H., Mayer, J., & Bruni, E. (2024). "A Review of Nine Physics Engines for Reinforcement Learning Research." arXiv preprint arXiv:2407.08590.
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GRASP: A Novel Benchmark for Evaluating Language Grounding and Situated Physics Understanding in Multimodal Language Models
Published in Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24, 2024
GRASP benchmark for evaluating language grounding and situated physics understanding in multimodal language models, presented at IJCAI-24.
Recommended citation: Jassim, S., Holubar, M., Richter, A., Wolff, C., Ohmer, X., & Bruni, E. (2024). "GRASP: A Novel Benchmark for Evaluating Language Grounding and Situated Physics Understanding in Multimodal Language Models." Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24, 6297-6305.
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Bidirectional Emergent Language in Situated Environments
Published in arXiv preprint arXiv:2408.14649, 2024
Research on bidirectional emergent language in situated environments, exploring how agents develop communication systems in interactive settings.
Recommended citation: Wolff, C., Mayer, J., Bruni, E., & Ohmer, X. (2024). "Bidirectional Emergent Language in Situated Environments." arXiv preprint arXiv:2408.14649.
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PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers
Published in arXiv preprint arXiv:2506.14842, 2025
PictSure: demonstrating the importance of pretraining embeddings for in-context learning image classifiers.
Recommended citation: Schiesser, L., Wolff, C., Haas, S., & Pukrop, S. (2025). "PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers." arXiv preprint arXiv:2506.14842.
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How well do LLMs reason over tabular data, really?
Published in 4th Table Representation Workshop - ACL 2025, 2025
Analysis of the reasoning capabilities of LLMs over tabular data, presented at the 4th Table Representation Workshop at ACL 2025.
Recommended citation: Wolff, C., & Hulsebos, M. (2025). "How well do LLMs reason over tabular data, really?" 4th Table Representation Workshop - ACL 2025.
MinervAI: Using Generative AI to Assist, Not Replace Humans in Peer Review
Published in AI in Science (AIS) 2025 – Copenhagen, Denmark, 2025
A position paper arguing for constrained, verifiable uses of LLMs in peer review and introducing MinervAI—an open-source tool that supports citation verification and argumentation mapping while preserving human judgment.
Recommended citation: Hüsing, I., Petersen, T., Weiher, M.-A., Wolff, C., & Musslick, S. (2025). MinervAI: Using Generative AI to Assist, Not Replace Humans in Peer Review. AI in Science (AIS) 2025.
Are We Asking the Right Questions? On Ambiguity in Natural Language Queries for Tabular Data Analysis
Published in AI for Tabular Data Workshop @ EuRIPS 2025, 2025
A conceptual framework for characterising ambiguity in natural-language queries over tabular data, arguing for cooperative query specification and analysing 15 common tabular-data benchmarks.
Recommended citation: Gomm, D., Wolff, C., & Hulsebos, M. (2025). Are We Asking the Right Questions? On Ambiguity in Natural Language Queries for Tabular Data Analysis. AI for Tabular Data Workshop at EuRIPS 2025.
SQALE: A Large Text-to-SQL Corpus Grounded in Real Schemas
Published in AI for Tabular Data Workshop @ Eurips 2025, 2025
Introduction of SQALE, a large-scale semi-synthetic text-to-SQL dataset grounded in real relational schemas, supporting research on scalable and generalizable NL2SQL models.
Recommended citation: Wolff, C., Gomm, D., & Hulsebos, M. SQaLe: A large text-to-SQL corpus grounded in real schemas. In EurIPS 2025 Workshop: AI for Tabular Data.
talks
teaching
Emergent Behavior in Multi-Agent Systems (EBIMAS)
Master's Study Project, Osnabrück University, 2022
Started and organized a study project to provide a platform and course setting for cutting edge Reinforcement Learning and emergent behavior research.
Study Project: LLMs for Science
Master's Study Project, Osnabrück University, 2024
Managed and organized a study project focused on “Supporting the Review Process with AI” - an AI-driven system developed by master’s students to assist with the academic reviewing process.