CogSciPrag homepage

Publications

2026

  1. van Tiel, B., Franke, M., Sauerland, U., & Geelhand, P. (2026). Bespoke Probabilistic Modelling Reveals Subtle Effects of Autism on Pragmatic Optimisation in the Expression of Quantification. Computational Brain & Behavior, 1–20.
  2. Warstadt, A., Agha, O., & Franke, M. (2026). Quantifying Epistemic Relevance. Open Mind, 10, 502–546.
  3. Imel, N., Futrell, R., Franke, M., & Zaslavsky, N. (2026). Agent-based imitation dynamics can yield efficiently compressed population-level vocabularies. ArXiv Preprint ArXiv:2603.15903.
  4. Tsvilodub, P., Klumpp, J.-F., Pour, A., Hu, J., & Franke, M. (2026). On Emergent Social World Models—Evidence for Functional Integration of Theory of Mind and Pragmatic Reasoning in Language Models. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 37382–37420.
  5. Tsvilodub, P., Mulligan, K., Snider, T., Hawkins, R. D., & Franke, M. (2026). Act or Clarify? Modeling Sensitivity to Uncertainty and Cost in Communication. Proceedings of the Annual Meeting of the Cognitive Science Society, 48.
  6. Tsvilodub, P., Carcassi, F., & Franke, M. (2026). Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives. ArXiv Preprint ArXiv:2607.18443. https://arxiv.org/abs/2607.18443
  7. Binz, M., Akata, E., Almaatouq, A., Alsobay, M., Ariasov, O., Brändle, F., Broska, D., Burton, J. W., Busch, N., Callaway, F., & others. (2026). Post-training makes large language models less human-like. ArXiv Preprint ArXiv:2605.07632. https://arxiv.org/pdf/2605.07632
  8. Adas, M., Tsvilodub, P., Franke, M., & Butz, M. V. (2026). Confirming Our Biases? Evaluating the Capabilities, Risks, and Societal Impact of Large Language Models. https://arxiv.org/abs/2608.06977
  9. Tsvilodub, P., Höth, M., Franke, M., Deiseroth, B., & Kauf, C. (2026). Rewarding Efficient Reasoning Improves Abstention on Underspecified Tasks in Reasoning Models. ArXiv Preprint ArXiv:2609.20846. https://arxiv.org/pdf/2609.20846
  10. Ying, L., Wu, J., Wang, Y. S., Aarya, S., Buschoff, L. M. S., Chen, H., Collins, K. M., de Varda, A., Fu, S., Houlihan, S. D., & others. (2026). CogGym: Towards Large-Scale Comparative Evaluation of Human and Machine Cognition. ArXiv Preprint ArXiv:2609.21259. https://arxiv.org/pdf/2609.21259
  11. Wang, H., Lassiter, D., & Franke, M. (2026). When Correlation means Causation: Pragmatic Factors modulate Causal Implicatures in Decision-Making Contexts. Proceedings of the Annual Meeting of the Cognitive Science Society, 48. https://escholarship.org/uc/item/8q26s1bh
  12. Fang, K., Guan, R. H., Wu, C. M., Franke, M., & Hawkins, R. (2026). Selective Truths: How Speakers Mislead and Listeners Miss It? Proceedings of the Annual Meeting of the Cognitive Science Society, 48. https://escholarship.org/uc/item/5804m2tm
  13. Carcassi, F., Wang, H., Cummins, C., & Franke, M. (2026). What guides utterance choice in argumentative language use? Proceedings of the Annual Meeting of the Cognitive Science Society, 48. https://escholarship.org/uc/item/2bq1d71z
  14. Waldis, A., Choshen, L., Hou, Y., & Perlitz, Y. (2026). Instructions Shape Production of Language, not Processing. ArXiv Preprint ArXiv:2605.11206.
  15. Štefánik, M., Mondorf, P., Waldis, A., Liu, Q., Yang, C., Spiegel, M., Kuchař, J., Kadlčı́k Marek, Vawda-Oomerjee, A., Liu, C., & others. (2026). AIMO Interpretability Challenge. ArXiv Preprint ArXiv:2607.13899.
  16. Tsvilodub, P., Waldis, A., Qiu, L., Linzen, T., & Franke, M. (2026). Bayesian Fine-tuning Yields Language Models that are as Bayesian as their Beliefs Allow. ArXiv Preprint ArXiv:2610.00679. https://arxiv.org/abs/2610.00679
  17. Mohammadpour, A., & Franke, M. (2026). Small transformers track Bayesian evidence for latent common causes via a context-invariant mechanism. ArXiv Preprint ArXiv:2609.35161. https://arxiv.org/abs/2609.35161

2025

  1. Achimova, A., Franke, M., & Butz, M. V. (2025). The alignment model of indirect communication. PloS One, 20(5), e0323839.
  2. Hu, J., Lepori, M. A., & Franke, M. (2025). Linking forward-pass dynamics in Transformers and real-time human processing. ArXiv Preprint ArXiv:2504.14107.
  3. Hawkins, R. D., Tsvilodub, P., Bergey, C. A., Goodman, N. D., & Franke, M. (2025). Relevant answers to polar questions. Philosophical Transactions B, 380(1932), 20230505.
  4. Tsvilodub, P., Hawkins, R. D., & Franke, M. (2025). Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering. Society for Computation in Linguistics, 8(1).
  5. Tsvilodub, P., Gandhi, K., Zhao, H., Fränken, J.-P., Franke, M., & Goodman, N. D. (2025). Non-literal understanding of number words by language models. Proceedings of the Annual Meeting of the Cognitive Science Society, 47. https://escholarship.org/uc/item/08c3s3jt
  6. Roettger, T. B., & Franke, M. (2025). Meaningful results for meaningful hypotheses: A tutorial on hypothesis testing with Bayes factors using ROPEs. PsyArXiv Preprint. https://osf.io/preprints/psyarxiv/6zsx3_v1
  7. Hu, J., Lepori, M. A., & Franke, M. (2025). Signatures of human-like processing in transformer forward passes. ArXiv Preprint ArXiv:2504.14107.

2024

  1. Yu, Q., Schlotterbeck, F., Wang, H., Reichmann, N., Stolterfoht, B., Eckardt, R., & Butt, M. (2024). Ad Hoc Compounds for Stance Detection. In A. Bhatia, G. Bouma, A. S. Doğruöz, K. Evang, M. Garcia, V. Giouli, L. Han, J. Nivre, & A. Rademaker (Eds.), Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024 (pp. 231–242). ELRA and ICCL. https://aclanthology.org/2024.mwe-1.27/
  2. Tsvilodub, P., Wang, H., Grosch, S., & Franke, M. (2024). Predictions from language models for multiple-choice tasks are not robust under variation of scoring methods. ArXiv Preprint ArXiv:2403.00998.
  3. Tsvilodub, P., Marty, P., Ramotowska, S., Romoli, J., & Franke, M. (2024). Experimental Pragmatics with Machines: Testing LLM Predictions for the Inferences of Plain and Embedded Disjunctions. ArXiv Preprint ArXiv:2405.05776.
  4. Lassiter, D., & Franke, M. (2024). The rationality of inferring causation from correlational language. Proceedings of the Annual Meeting of the Cognitive Science Society, 46.
  5. Franke, M., Bohn, M., & Fröhlich, M. (2024). Latent meaning representations in great-ape gestural communication. Proceedings of the Annual Meeting of the Cognitive Science Society, 46.
  6. Franke, M., Tsvilodub, P., & Carcassi, F. (2024). Bayesian Statistical Modeling with Predictors from LLMs. ArXiv Preprint ArXiv:2406.09012.
  7. Tsvilodub, P., Franke, M., & Carcassi, F. (2024). Cognitive Modeling with Scaffolded LLMs: A Case Study of Referential Expression Generation. ArXiv Preprint ArXiv:2407.03805.
  8. Macuch Silva, V., Lorson, A., Franke, M., Cummins, C., & Winter, B. (2024). Strategic use of English quantifiers in the reporting of quantitative information. Discourse Processes, 61(10), 498–523.
  9. Hu, J., & Franke, M. (2024). Deep and shallow thinking in a single forward pass. NeurIPS 2024 Workshop on Behavioral Machine Learning.
  10. Snider, T., & Franke, M. (2024). Modeling uncertainty, unawareness, and underspecification among Structural Causal Models. Proceedings of Sinn Und Bedeutung, 29, 1484–1500.

2023

  1. Hawkins, R. D., Franke, M., Frank, M. C., Goldberg, A. E., Smith, K., Griffiths, T. L., & Goodman, N. D. (2023). From partners to populations: A hierarchical Bayesian account of coordination and convention. Psychological Review, 130(4), 977.
  2. Coretta, S., Casillas, J. V., Roessig, S., Franke, M., Ahn, B., Al-Hoorie, A. H., Al-Tamimi, J., Alotaibi, N. E., AlShakhori, M. K., Altmiller, R. M., & others. (2023). Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human-speech analyses. Advances in Methods and Practices in Psychological Science, 6(3), 25152459231162567.
  3. Tsvilodub, P., & Franke, M. (2023). Evaluating pragmatic abilities of image captioners on a3ds. ArXiv Preprint ArXiv:2305.12777.
  4. Carcassi, F., & Franke, M. (2023). How to handle the truth: A model of politeness as strategic truth-stretching. Proceedings of the Annual Meeting of the Cognitive Science Society, 45(45).
  5. Tsvilodub, P., Franke, M., Hawkins, R. D., & Goodman, N. D. (2023). Overinformative question answering by humans and machines. ArXiv Preprint ArXiv:2305.07151.
  6. Tsvilodub, P., van Tiel, B., & Franke, M. (2023). The role of relevance, competence, and priors for scalar inferences. Experiments in Linguistic Meaning, 2, 288–298.
  7. Grusdt, B., Liu, M., & Franke, M. (2023). Testing the influence of QUDs on the occurrence of Conditional Perfection. Experiments in Linguistic Meaning, 2, 104–116.

2022

  1. Ohmer, X., Marino, M., Franke, M., & König, P. (2022). Mutual influence between language and perception in multi-agent communication games. PLoS Computational Biology, 18(10), e1010658.
  2. van Tiel, B., Sauerland, U., & Franke, M. (2022). Meaning and use in the expression of estimative probability. Open Mind, 6, 250–263.
  3. Rohde, H., Hoek, J., Keshev, M., & Franke, M. (2022). This better be interesting: A speaker’s decision to speak cues listeners to expect informative content. Open Mind, 6, 118–131.

2021

  1. Grusdt, B., Lassiter, D., & Franke, M. (2021). Probabilistic modeling of rational communication with conditionals. ArXiv Preprint ArXiv:2105.05502.