41 citations · 53 across the 17 of their papers we have counts for
9 papers · 1 filter
CogGym: Towards Large-Scale Comparative Evaluation of Human and Machine Cognition
Lance Ying, Jinzhou Wu, Yingshan Susan Wang +53
Understanding and modeling human intelligence are parallel goals shared by artificial intelligence (AI) and cognitive science. As AI systems grow increasingly capable, in what ways…
Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans
Akshay K. Jagadish, Younes Strittmatter, Nori Jacoby +4
Behavioral foundation models have been proposed as stand-ins for human participants across settings, but it is unclear whether theories discovered on them generalize to humans or m…
More accurate behavioral predictions with hybrid Bayesian-connectionist models
Brenden M. Lake, Akshay K. Jagadish, Guangyuan Jiang
Researchers must often choose between Bayesian or neural network models of behavior, two paradigms with complementary strengths and weaknesses. An ideal paradigm would facilitate t…
Closing the Loop to Discover Psychological Theories with an Automated Cognitive Scientist
Akshay K. Jagadish, Younes Strittmatter, Nori Jacoby +5
Across the sciences, autonomous systems are increasingly being used in closed-loop discovery, proposing new theories and designing and running experiments to test them. This approa…
Using Probabilistic Programs to Train Inductive Reasoning in Large Language Models
Liyi Zhang, Akshay K. Jagadish, Brenden M. Lake +1
Post-training Large Language Models (LLMs) for reasoning typically focuses on deductive tasks such as mathematics and coding where correctness is verifiable. Yet, many real-world r…
Post-training makes large language models less human-like
Marcel Binz, Elif Akata, Abdullah Almaatouq +76
Large language models (LLMs) are increasingly used as surrogates for human participants, but it remains unclear which models best capture human behavior and why. To address this, w…
Think-Aloud Reshapes Automated Cognitive Model Discovery Beyond Behavior
Hanbo Xie, Akshay K. Jagadish, Lan Pan +1
Computational cognitive models discovered using large language models have so far relied solely on behavioral data. However, it is well-known that models produced from the behavior…
Automated Adversarial Collaboration for Advancing Theory Building in the Cognitive Sciences
Suyog Chandramouli, George Kachergis, Akshay Jagadish
Cognitive science often evaluates theories through narrow paradigms and local model comparisons, limiting the integration of evidence across tasks and realizations. We introduce an…
Toward an automated science of the mind
Akshay K. Jagadish, Milena Rmus, Kristin Witte +3
Artificial Intelligence is starting to automate scientific discovery, raising the prospect of an automated science of the mind. We chart this field around four challenges: represen…