Publications

Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tešić, Rakshit S. Trivedi, Alexander Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P. Agapiou, Jayd Matyas, Danny Karmon, Dylan Hadfield-Menell, Natasha Jaques, Tim Baarslag, José Hernández-Orallo, Joel Z. Leibo, Concordia contest participants (2025). Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia. NeurIPS 2025 Track on Datasets and Benchmarks.

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Marko Tešić, Yue Zhao, Joel Z. Leibo, Rakshit S. Trivedi, José Hernández-Orallo (2025). Beyond the high score: Prosocial ability profiles of multi-agent populations. Preprint.

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Marko Tešić, John Burden, Lorenzo Pacchiardi, José Hernández-Orallo (2025). Paradigms of AI Evaluation: Mapping Goals, Methodologies and Culture. IJCAI-25 Survey Track.

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Marko Tešić, Janet Slesinski (2025). Benchmark Design Criteria for Mathematical Reasoning in LLMs. Center for Curriculum Redesign.

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Marko Tešić, Lorenzo Pacchiardi, Lucy Cheke, José Hernández-Orallo (2024). Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers. Preprint.

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Matteo Gabriel Mecattaf, Ben Slater, Marko Tešić, Jonathan Prunty, Konstantinos Voudouris, Lucy Cheke (2024). A little less conversation, a little more action, please: Investigating the physical common-sense of LLMs in a 3D embodied environment. Preprint.

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Rakshit S. Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar A. Duéñez-Guzmán, John P. Agapiou, Jayd Matyas, Sasha Vezhnevets, Dipam Chakraborty, Yue Zhao, Marko Tešić, Barna Pásztor, Yunke Ao, Omar G. Younis, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Mian Deng, Ziwei Deng, Utku Erdoğanaras, Natasha Jaques, Jakob Nicolaus Foerster, Vincent Conitzer, José Hernández-Orallo, Dylan Hadfield-Menell, Joel Z. Leibo (2024). Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. NeurIPS 2024 Track on Datasets and Benchmarks.

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Rafael Fuchs, Marko Tešić, Ulrike Hahn (2024). Testing the maximum entropy approach to awareness growth in Bayesian epistemology and decision theory. Proceedings of the 46th Annual Meeting of the Cognitive Science Society.

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Marko Tešić, Ulrike Hahn (2023). The impact of explanations as communicative acts on belief in a claim: The role of source reliability. Cognition.

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Ulrike Hahn, Marko Tešić (2023). Argument and explanation. Philosophical Transactions of the Royal Society A.

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Marko Tešić, Ulrike Hahn (2022). Can counterfactual explanations of AI systems’ predictions skew lay users’ causal intuitions about the world? If so, can we correct for that?. Patterns.

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Marko Tešić (2021). On the transferability of insights from the psychology of explanation to explainable AI. Human Centered AI workshop at NeurIPS 2021.

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Marko Tešić, Ulrike Hahn (2021). Explanation in AI systems. Human-Like Machine Intelligence.

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Marko Tešić, Alice Liefgreen, David Lagnado (2020). The propensity interpretation of probability and diagnostic split in explaining away. Cognitive Psychology.

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Nicole Cruz, Saoirse Connor Desai, Stephen Dewitt, Ulrike Hahn, David Lagnado, Alice Liefgreen, Kirsty Phillips, Toby Pilditch, Marko Tešić (2020). Widening Access to Bayesian Problem Solving. Frontiers in Psychology.

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Marko Tešić, Ulrike Hahn (2019). Sequential diagnostic reasoning with independent causes. Proceedings of the 41th Annual Meeting of the Cognitive Science Society.

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Alice Liefgreen, Marko Tešić, David Lagnado (2018). Explaining away: Significance of priors, diagnostic reasoning, and structural complexity. Proceedings of the 40th Annual Meeting of the Cognitive Science Society.

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Marko Tešić, Benjamin Eva, Stephan Hartmann (2017). Confirmation by Explanation: A Bayesian Justification of IBE. Preprint.

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Marko Tešić (2017). Confirmation and the Generalized Nagel-Schaffner Model of Reduction: A Bayesian Analysis. Synthese.

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