Akshay K. Jagadish

According to our database, Akshay K. Jagadish authored at least 7 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Centaur: a foundation model of human cognition.

Marcel Binz, Elif Akata, Matthias Bethge, Franziska Brändle, Fred Callaway, Julian Coda-Forno, Peter Dayan, Can Demircan, Maria K. Eckstein, Noémi Élteto, Thomas L. Griffiths, Susanne Haridi, Akshay K. Jagadish, Li Ji-An, Alexander Kipnis, Sreejan Kumar, Tobias Ludwig, Marvin Mathony, Marcelo G. Mattar, Alireza Modirshanechi, Surabhi S. Nath, Joshua C. Peterson, Milena Rmus, Evan M. Russek, Tankred Saanum, Natalia Scharfenberg, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert Wilson, Kristin Witte, Shuchen Wu, Dirk Wulff, Huadong Xiong, Eric Schulz

CoRR, 2024

Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models.

Can Demircan, Tankred Saanum, Akshay K. Jagadish, Marcel Binz, Eric Schulz

CoRR, 2024

Ecologically rational meta-learned inference explains human category learning.

Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann, Eric Schulz, Marcel Binz

CoRR, 2024

In-Context Learning Agents Are Asymmetric Belief Updaters.

Johannes A. Schubert, Akshay K. Jagadish, Marcel Binz, Eric Schulz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks.

Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann, Eric Schulz, Marcel Binz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Inducing anxiety in large language models increases exploration and bias.

Julian Coda-Forno, Kristin Witte, Akshay K. Jagadish, Marcel Binz, Zeynep Akata, Eric Schulz

CoRR, 2023

Meta-Learned Models of Cognition.

Marcel Binz, Ishita Dasgupta, Akshay K. Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz

CoRR, 2023