Publications of Dirk U. Wulff

Thesis - PhD (2)

2024
Thesis - PhD
Aeschbach, S. (2024). Advancing models of semantic representation: Empirical study designs, network analysis methods, and computational tools [PhD Thesis, Universität Basel].
(published online 2025: https://doi.org/10.5451/unibas-ep96849).
2015
Thesis - PhD
Wulff, D. U. (2015). Information search in experience-based choice and valuation: Challenges and applications [PhD Thesis, Universität Basel].

Issue (1)

2020
Issue
Kenett, Y. N., Beckage, N. M., Siew, C. S. Q., & Wulff, D. U. (Eds.). (2020). Cognitive network science: A new frontier [Special issue]. Complexity, .

Preprint (10)

2025
Preprint
Bentz, D., & Wulff, D. U. (2025). Mapping OCD symptom triggers with large language models. MedRxiv, May 16, 2025. https://doi.org/10.1101/2025.05.15.25327706
Preprint
Hussain, Z., Mata, R., & Wulff, D. U. (2025). A rebuttal of two common deflationary stances against LLM cognition (Version posted online June 09, 2025). OSF Preprints, February 16, 2025. https://doi.org/10.31219/osf.io/y34ur_v2
Preprint
Tiede, K. E., Hertwig, R., Mata, R., & Wulff, D. U. (2025). Boosting risk communication with experiential simulations. PsyArXiv, June 20, 2025. https://doi.org/10.31234/osf.io/t7enc_v1
Preprint
Wulff, D. U., & Mata, R. (2025). Escaping the jingle-jangle jungle: Increasing conceptual clarity in psychology using large language models. PsyArXiv, April 30, 2025. https://doi.org/10.31234/osf.io/ksuh8_v1
2024
Preprint
Aeschbach, S., Mata, R., & Wulff, D. U. (2024). Measuring individual semantic networks: A simulation study. arXiv, 2410.18326. https://doi.org/10.48550/arXiv.2410.18326
Preprint
Hussain, Z., Mata, R., Newell, B. R., & Wulff, D. U. (2024). Probing the contents of semantic representations from text, behavior, and brain data using the psychNorms metabase. arXiv, 2412.04936. https://doi.org/10.48550/arXiv.2412.04936
Preprint
Wulff, D. U., Hussain, Z., & Mata, R. (2024). The behavioral and social sciences need open LLMs. OSF Preprints, September 04, 2024. https://doi.org/10.31219/osf.io/ybvzs