Marcel Binz - RankMe

41 papers A* 10B 7Journal 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Can we automatize scientific discovery in the cognitive sciences? CoRR Akshay K. Jagadish, Milena Rmus, Kristin Witte, Marvin Mathony, Marcel Binz, Eric Schulz
2025	J	`jnl`	A foundation model to predict and capture human cognition. Nat. 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, Ji-An Li, 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, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert C. Wilson, Kristin Witte, Shuchen Wu, Dirk U. Wulff, Huadong Xiong, Eric Schulz
2025	J	`jnl`	Automated scientific minimization of regret. CoRR Marcel Binz, Akshay K. Jagadish, Milena Rmus, Eric Schulz
2025	B	`conf`	Bounded Ecologically Rational Meta-learned Inference Explains Human Category Learning. CogSci Akshay Kumar Jagadish, Julian Coda-Forno, Mirko Thalmann, Marcel Binz, Eric Schulz
2025	J	`jnl`	Meta-learning ecological priors from large language models explains human learning and decision making. CoRR Akshay K. Jagadish, Mirko Thalmann, Julian Coda-Forno, Marcel Binz, Eric Schulz
2025	A*	`conf`	Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. ICLR Can Demircan, Tankred Saanum, Akshay Kumar Jagadish, Marcel Binz, Eric Schulz
2025	J	`jnl`	metabeta - A fast neural model for Bayesian mixed-effects regression. CoRR Alexander Kipnis, Marcel Binz, Eric Schulz
2024	J	`jnl`	Centaur: a foundation model of human cognition. CoRR 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, Ji-An Li, 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 C. Wilson, Kristin Witte, Shuchen Wu, Dirk U. Wulff, Huadong Xiong, Eric Schulz
2024	A*	`conf`	CogBench: a large language model walks into a psychology lab. ICML Julian Coda-Forno, Marcel Binz, Jane X. Wang, Eric Schulz
2024	J	`jnl`	CogBench: a large language model walks into a psychology lab. CoRR Julian Coda-Forno, Marcel Binz, Jane X. Wang, Eric Schulz
2024	J	`jnl`	Ecologically rational meta-learned inference explains human category learning. CoRR Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann, Eric Schulz, Marcel Binz
2024	A*	`conf`	Evaluating alignment between humans and neural network representations in image-based learning tasks. NeurIPS Can Demircan, Tankred Saanum, Leonardo Pettini, Marcel Binz, Blazej M. Baczkowski, Christian F. Doeller, Mona M. Garvert, Eric Schulz
2024	B	`conf`	Higher cognition in large language models. CogSci Nicholas Ichien, Sudeep Bhatia, Anna A. Ivanova, Taylor W. Webb, Tom Griffiths, Marcel Binz
2024	A*	`conf`	Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks. ICML Akshay K. Jagadish, Julian Coda-Forno, Mirko Thalmann, Eric Schulz, Marcel Binz
2024	A*	`conf`	In-Context Learning Agents Are Asymmetric Belief Updaters. ICML Johannes A. Schubert, Akshay K. Jagadish, Marcel Binz, Eric Schulz
2024	J	`jnl`	In-context learning agents are asymmetric belief updaters. CoRR Johannes A. Schubert, Akshay K. Jagadish, Marcel Binz, Eric Schulz
2024	B	`conf`	In-context learning in natural and artificial intelligence. CogSci Akshay Kumar Jagadish, Ishita Dasgupta, Jacques Pesnot Lerousseau, Marcel Binz
2024	J	`jnl`	Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. CoRR Can Demircan, Tankred Saanum, Akshay K. Jagadish, Marcel Binz, Eric Schulz
2024	A*	`conf`	Turning large language models into cognitive models. ICLR Marcel Binz, Eric Schulz
2023	J	`jnl`	How should the advent of large language models affect the practice of science? CoRR Marcel Binz, Stephan Alaniz, Adina Roskies, Balazs Aczel, Carl T. Bergstrom, Colin Allen, Daniel Schad, Dirk U. Wulff, Jevin D. West, Qiong Zhang, Richard M. Shiffrin, Samuel J. Gershman, Ven Popov, Emily M. Bender, Marco Marelli, Matthew M. Botvinick, Zeynep Akata, Eric Schulz
2023	J	`jnl`	Inducing anxiety in large language models increases exploration and bias. CoRR Julian Coda-Forno, Kristin Witte, Akshay K. Jagadish, Marcel Binz, Zeynep Akata, Eric Schulz
2023	J	`jnl`	Language Aligned Visual Representations Predict Human Behavior in Naturalistic Learning Tasks. CoRR Can Demircan, Tankred Saanum, Leonardo Pettini, Marcel Binz, Blazej M. Baczkowski, Paula Kaanders, Christian F. Doeller, Mona M. Garvert, Eric Schulz
2023	J	`jnl`	Meta-Learned Models of Cognition. CoRR Marcel Binz, Ishita Dasgupta, Akshay K. Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz
2023	A*	`conf`	Meta-in-context learning in large language models. NeurIPS Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matt M. Botvinick, Jane X. Wang, Eric Schulz
2023	J	`jnl`	Meta-in-context learning in large language models. CoRR Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matthew M. Botvinick, Jane X. Wang, Eric Schulz
2023	A*	`conf`	Reinforcement Learning with Simple Sequence Priors. NeurIPS Tankred Saanum, Noémi Élteto, Peter Dayan, Marcel Binz, Eric Schulz
2023	J	`jnl`	Reinforcement Learning with Simple Sequence Priors. CoRR Tankred Saanum, Noémi Élteto, Peter Dayan, Marcel Binz, Eric Schulz
2023	A*	`conf`	The Acquisition of Physical Knowledge in Generative Neural Networks. ICML Luca M. Schulze Buschoff, Eric Schulz, Marcel Binz
2023	J	`jnl`	The Acquisition of Physical Knowledge in Generative Neural Networks. CoRR Luca M. Schulze Buschoff, Eric Schulz, Marcel Binz
2023	J	`jnl`	Turning large language models into cognitive models. CoRR Marcel Binz, Eric Schulz
2022	B	`conf`	Decision-Making with Naturalistic Options. CogSci Can Demircan, Leonardo Pettini, Tankred Saanum, Marcel Binz, Blazej M. Baczkowski, Christian F. Doeller, Mona M. Garvert, Eric Schulz
2022	J	`jnl`	Exploration With a Finite Brain. CoRR Marcel Binz, Eric Schulz
2022	A*	`conf`	Modeling Human Exploration Through Resource-Rational Reinforcement Learning. NeurIPS Marcel Binz, Eric Schulz
2022	J	`jnl`	Stochastic Gradient Descent Captures How Children Learn About Physics. CoRR Luca M. Schulze Buschoff, Eric Schulz, Marcel Binz
2022	J	`jnl`	Using cognitive psychology to understand GPT-3. CoRR Marcel Binz, Eric Schulz
2021	—	`—`	Principles of Human Learning. Marcel Binz
2019	B	`conf`	Emulating Human Developmental Stages with Bayesian Neural Networks. CogSci Marcel Binz, Dominik M. Endres
2019	J	`jnl`	Emulating Human Developmental Stages with Bayesian Neural Networks. CoRR Marcel Binz, Dominik M. Endres
2019	B	`conf`	Where Do Heuristics Come From? CogSci Marcel Binz, Dominik M. Endres
2019	J	`jnl`	Where Do Human Heuristics Come From? CoRR Marcel Binz, Dominik M. Endres
2016	B	`conf`	Is it Living? Insights from Modeling Event-Oriented, Self-Motivated, Acting, Learning and Conversing Game Agents. CogSci Martin V. Butz, Mihael Simonic, Marcel Binz, Jonas Einig, Stephan Ehrenfeld, Fabian Schrodt