| 2025 | CogSci | Resource-rational belief revision can mitigate as well as amplify polarization. | Rebekah Gelpi, Pablo Len-Villagr, William A. Cunningham, Christopher Guy Lucas, Daphna Buchsbaum |
| 2025 | CogSci | The emergence of flexible perspective reasoning in large language models. | Pablo Len-Villagr, Tiana V. Simovic, Craig G. Chambers |
| 2025 | CogSci | Examining Individual Differences in Within-Category Variability Reasoning. | Olympia N. Mathiaparanam, Pablo Len-Villagr, Daphna Buchsbaum, Karl S. Rosengren |
| 2024 | CogSci | People Need About Five Seconds to be Random: Autocorrelated Sampling Algorithms Can Explain Why. | Lucas Castillo, Pablo Len-Villagr, Johanna Falben, Nick Chater, Adam Sanborn |
| 2024 | CogSci | Randomly Generating Stereotypes: Can We Understand Implicit Attitudes with Random Generation? | Johanna Falben, Lucas Castillo, Pablo Len-Villagr, Nick Chater, Adam Sanborn |
| 2024 | CogSci | How Red Is a Ladybeetle? Examining People's Notions of Biological Variability. | Pablo Len-Villagr, Olympia N. Mathiaparanam, Karl S. Rosengren, Daphna Buchsbaum |
| 2024 | CogSci | Self induced framing as a cognitive strategy for decision-making. | Marc-Llus Vives, Pablo Len-Villagr |
| 2023 | CogSci | The Impact of Production Rates on Sequential Statistics and Distributional Properties in Random Generation. | Pablo Len-Villagr, Lucas Castillo, Nick Chater, Adam Sanborn |
| 2023 | CogSci | Charting children's fruit categories with Markov-Chain Monte Carlo with People. | Pablo Len-Villagr, Isaac Ehrlich, Chris Lucas, Daphna Buchsbaum |
| 2023 | EMNLP | Large Language Models are biased to overestimate profoundness. | Eugenio Herrera-Berg, Toms Vergara Browne, Pablo Len-Villagr, Marc-Llus Vives, Cristian Buc Calderon |
| 2022 | CogSci | Eliciting Human Beliefs using Random Generation. | Pablo Len-Villagr, Lucas Castillo, Nick Chater, Adam Sanborn |
| 2022 | CogSci | Uncovering children's concepts and conceptual change. | Pablo Len-Villagr, Isaac Ehrlich, Chris Lucas, Daphna Buchsbaum |
| 2022 | CogSci | Uncovering Childrens' Category Representations with MCMCP. | Pablo Len-Villagr, Isaac Ehrlich, Chris Lucas, Daphna Buchsbaum |
| 2021 | CogSci | Local Sampling with Momentum Accounts for Human Random Sequence Generation. | Lucas Castillo, Pablo Len-Villagr, Nicholas Chater, Adam Sanborn |
| 2021 | CogSci | Sampling Associations with (Un)related Suggestions. | Pablo Len-Villagr, Nicholas Chater, Adam Sanborn |
| 2021 | CogSci | Recovering human category structure across development using sparse judgments. | Pablo Len-Villagr, Isaac Ehrlich, Chris Lucas, Daphna Buchsbaum |
| 2020 | CogSci | Exploring Category Structure in Children and Adults. | Pablo Len-Villagr, Isaac Ehrlich, Chris Lucas, Daphna Buchsbaum |
| 2020 | CogSci | Uncovering Category Representations with Linked MCMC with People. | Pablo Len-Villagr, Kay Otsubo, Chris Lucas, Daphna Buchsbaum |
| 2019 | CogSci | Exploring the Representation of Linear Functions. | Pablo Len-Villagr, Verena Klar, Adam Sanborn, Chris Lucas |
| 2019 | CogSci | Generalizing Functions in Sparse Domains. | Pablo Len-Villagr, Chris Lucas |
| 2018 | CogSci | Data Availability and Function Extrapolation. | Pablo Len-Villagr, Irina Preda, Christopher Lucas |
| 2017 | CogSci | Identifying Causal Direction in the Two-Variable Case. | Pablo Len-Villagr, Christopher Lucas |
| 2013 | CogSci | Categorization and Abstract Similarity in Chess. | Pablo Len-Villagr, Frank Jkel |