Taylor W. Webb

According to our database, Taylor W. Webb authored at least 37 papers between 2016 and 2026.

Collaborative distances:

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

2026

Binding Visual Features Point by Point.

Udith Haputhanthri, Declan Campbell, Rim Assouel, Jonathan D. Cohen, Taylor W. Webb

CoRR, May, 2026

2025

Visual serial processing deficits explain divergences in human and VLM reasoning.

Nicholas Budny, Kia Ghods, Declan Campbell, Raja Marjieh, Amogh Joshi, Sreejan Kumar, Jonathan D. Cohen, Taylor W. Webb, Thomas L. Griffiths

CoRR, September, 2025

Whither symbols in the era of advanced neural networks?

Thomas L. Griffiths, Brenden M. Lake, R. Thomas McCoy, Ellie Pavlick, Taylor W. Webb

CoRR, August, 2025

Engineering Sentience.

Konstantin Demin, Taylor W. Webb, Eric Elmoznino, Hakwan Lau

CoRR, June, 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

Caption This, Reason That: VLMs Caught in the Middle.

Zihan Weng, Lucas Gomez, Taylor Whittington Webb, Pouya Bashivan

CoRR, May, 2025

Evaluating Compositional Scene Understanding in Multimodal Generative Models.

Shuhao Fu, Andrew Jun Lee, Anna Wang, Ida Momennejad, Trevor Bihl, Hongjing Lu, Taylor Whittington Webb

Trans. Mach. Learn. Res., 2025

Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language Models.

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Position: We Need An Algorithmic Understanding of Generative AI.

Oliver Eberle, Thomas McGee, Hamza Giaffar, Taylor Whittington Webb, Ida Momennejad

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Non-linear relational composition in large language models.

Michael B. McCoy, Taylor W. Webb, Anna Leshinskaya

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Cognitively Inspired Interpretability in Large Neural Networks.

Anna Leshinskaya, Taylor W. Webb, Ellie Pavlick, Jiahai Feng, Gustaw Opielka, Claire E. Stevenson, Idan A. Blank

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Few-Shot Learning of Visual Compositional Concepts through Probabilistic Schema Induction.

Andrew Jun Lee, Taylor W. Webb, Trevor Bihl, Keith J. Holyoak, Hongjing Lu

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

How do LLMs Solve Multi-step Reasoning? An Algorithmic Evaluation.

Oliver Eberle, Thomas McGee, Hamza Giaffar, Taylor W. Webb, Ida Momennejad

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

2024

Evidence from counterfactual tasks supports emergent analogical reasoning in large language models.

Taylor W. Webb, Keith J. Holyoak, Hongjing Lu

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 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Slot Abstractors: Toward Scalable Abstract Visual Reasoning.

Shanka Subhra Mondal, Jonathan D. Cohen, Taylor Whittington Webb

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

Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers.

Awni Altabaa, Taylor Whittington Webb, Jonathan D. Cohen, John Lafferty

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Higher cognition in large language models.

Nicholas Ichien, Sudeep Bhatia, Anna A. Ivanova, Taylor W. Webb, Tom Griffiths, Marcel Binz

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

2023

A Prefrontal Cortex-inspired Architecture for Planning in Large Language Models.

Taylor W. Webb, Shanka Subhra Mondal, Chi Wang, Brian Krabach, Ida Momennejad

CoRR, 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

Determinantal Point Process Attention Over Grid Codes Supports Out of Distribution Generalization.

Shanka Subhra Mondal, Steven Frankland, Taylor W. Webb, Jonathan D. Cohen

CoRR, 2023

Abstractors: Transformer Modules for Symbolic Message Passing and Relational Reasoning.

Awni Altabaa, Taylor W. Webb, Jonathan D. Cohen, John Lafferty

CoRR, 2023

Systematic Visual Reasoning through Object-Centric Relational Abstraction.

Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to reason over visual objects.

Shanka Subhra Mondal, Taylor Whittington Webb, Jonathan Cohen

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Emergent Analogical Reasoning in Large Language Models.

Taylor W. Webb, Keith J. Holyoak, Hongjing Lu

CoRR, 2022

Zero-shot visual reasoning through probabilistic analogical mapping.

Taylor W. Webb, Shuhao Fu, Trevor Bihl, Keith J. Holyoak, Hongjing Lu

CoRR, 2022

2021

Emergent Symbols through Binding in External Memory.

Taylor Whittington Webb, Ishan Sinha, Jonathan D. Cohen

Proceedings of the 9th International Conference on Learning Representations, 2021

A Task-Optimized Neural Network Model of Decision Confidence.

Taylor W. Webb, Kiyofumi Miyoshi, Tsz Yan So, Hakwan Lau

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

Modelling the development of counting with memory-augmented neural networks.

Zack Dulberg, Taylor W. Webb, Jonathan Cohen

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

A Memory-Augmented Neural Network Model of Abstract Rule Learning.

Ishan Sinha, Taylor W. Webb, Jonathan D. Cohen

CoRR, 2020

Learning Representations that Support Extrapolation.

Taylor W. Webb, Zachary Dulberg, Steven Frankland, Alexander A. Petrov, Randall C. O'Reilly, Jonathan Cohen

Proceedings of the 37th International Conference on Machine Learning, 2020

A memory-augmented neural network model of abstract sequential reasoning.

Ishan Sinha, Jonathan Cohen, Taylor W. Webb

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

2019

A tradeoff between generalization and perceptual capacity in recurrent neural networks.

Taylor W. Webb, Steven Frankland, Simon N. Segert, Alexander A. Petrov, Randall C. O'Reilly, Jonathan Cohen

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Understanding interactions amongst cognitive control, learning and representation.

Sebastian Musslick, Abigail Novick Hoskin, Taylor W. Webb, Steven Frankland, Jonathan D. Cohen, Rebecca L. Jackson, Matthew A. Lambon Ralph, Lang Chen, Timothy T. Rogers, Randall C. O'Reilly, Alexander A. Petrov

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Extracting and Utilizing Abstract, Structured Representations for Analogy.

Steven Frankland, Taylor W. Webb, Alexander A. Petrov, Randall C. O'Reilly, Jonathan Cohen

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2016

Effects of Awareness on the Control of Attention.

Taylor W. Webb, Hope H. Kean, Michael S. A. Graziano

J. Cogn. Neurosci., 2016