Declan Campbell

According to our database, Declan Campbell authored at least 12 papers between 2020 and 2025.

Collaborative distances:

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

2025

Visual symbolic mechanisms: Emergent symbol processing in vision language models.

Rim Assouel, Declan Campbell, Taylor W. Webb

CoRR, June, 2025

Bound by semanticity: universal laws governing the generalization-identification tradeoff.

Marco Nurisso, Jesseba Fernando, Raj Deshpande, Alan Perotti, Raja Marjieh, Steven M. Frankland, Richard L. Lewis, Taylor W. Webb, Declan Campbell, Francesco Vaccarino, Jonathan D. Cohen, Giovanni Petri

CoRR, June, 2025

Understanding Task Representations in Neural Networks via Bayesian Ablation.

Andrew Nam, Declan Campbell, Thomas L. Griffiths, Jonathan D. Cohen, Sarah-Jane Leslie

CoRR, May, 2025

Using the Tools of Cognitive Science to Understand Large Language Models at Different Levels of Analysis.

Alexander Ku, Declan Campbell, Xuechunzi Bai, Jiayi Geng, Ryan Liu, Raja Marjieh, R. Thomas McCoy, Andrew Nam, Ilia Sucholutsky, Veniamin Veselovsky, Liyi Zhang, Jian-Qiao Zhu, Thomas L. Griffiths

CoRR, March, 2025

Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models.

Yukang Yang, Declan Campbell, Kaixuan Huang, Mengdi Wang, Jonathan D. Cohen, Taylor W. Webb

CoRR, February, 2025

2024

Using Contrastive Learning with Generative Similarity to Learn Spaces that Capture Human Inductive Biases.

Raja Marjieh, Sreejan Kumar, Declan Campbell, Liyi Zhang, Gianluca M. Bencomo, Jake Snell, Thomas L. Griffiths

CoRR, 2024

A Relational Inductive Bias for Dimensional Abstraction in Neural Networks.

Declan Campbell, Jonathan D. Cohen

CoRR, 2024

Human-Like Geometric Abstraction in Large Pre-trained Neural Networks.

Declan Campbell, Sreejan Kumar, Tyler Giallanza, Thomas L. Griffiths, Jonathan D. Cohen

CoRR, 2024

Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction.

Sreejan Kumar, Raja Marjieh, Byron Zhang, Declan Campbell, Michael Y. Hu, Umang Bhatt, Brenden M. Lake, Thomas L. Griffiths

CoRR, 2024

Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem.

Declan Campbell, Sunayana Rane, Tyler Giallanza, Nicolò De Sabbata, Kia Ghods, Amogh Joshi, Alexander Ku, Steven Frankland, Tom Griffiths, Jonathan D. Cohen, Taylor W. Webb

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

The Relational Bottleneck as an Inductive Bias for Efficient Abstraction.

Taylor W. Webb, Steven M. Frankland, Awni Altabaa, Kamesh Krishnamurthy, Declan Campbell, Jacob L. Russin, Randall C. O'Reilly, John Lafferty, Jonathan D. Cohen

CoRR, 2023

2020

Disentangling Generativity in Visual Cognition.

Declan Campbell, Timothy T. Rogers

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020