Publications

Peer-reviewed Publications

• Yulia Zinova, David Arps, Katharina Spalek, Jacopo Romoli. Linking Language Model Predictions to Human Behaviour on Scalar Implicatures. Bridging Neurons and Symbols @ COLING, 2025.
• Renato Vukovic, David Arps, Carel van Niekerk, Benjamin Matthias Ruppik, Hsien-Chin Lin, Michael Heck, Milica Gašić. Dialogue Ontology Relation Extraction via Constrained Chain-of-Thought Decoding. SIGDIAL, 2024.
• Arps, David, Laura Kallmeyer, Younes Samih, Hassan Sajjad. Multilingual Nonce Dependency Treebanks: Understanding How Language Models Represent and Process Syntactic Structure. NAACL, 2024.
• Omar Momen, David Arps, Laura Kallmeyer. Increasing the Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building. BabyLM Shared Task at CoNLL, 2023.
• Arps, David, Younes Samih, Laura Kallmeyer, Hassan Sajjad. Probing for Constituency Structure in Neural Language Models. EMNLP Findings, 2022.
• Arps, David, Jan Kels, Florian Krämer, Yunus Renz, Regina Stodden, Wiebke Petersen. HHUplexity at Text Complexity DE Challenge 2022. GermEval 2022 Workshop on Text Complexity Assessment of German Text, 2022.
• Arps, David, Simon Petitjean. A Parser for LTAG and Frame Semantics. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 2018.

Preprints

• Arps, David, Hassan Sajjad, Laura Kallmeyer. Understanding Syntactic Generalization in Structure-Inducing Language Models. arXiv, 2025.
• Sri Harsha Dumpala, David Arps, Sageev Oore, Laura Kallmeyer, Hassan Sajjad. Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Models. arXiv, 2024.