A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks | Paper Citation Record

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This paper cites Elsevier, New York and London (1973).

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Elsevier, New York and London (1973)

Reference 1

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This paper cites The bulletin of mathematical biophysics 5(4), 115–133 (1943) https: //doi.org/10.1007/bf02478259.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks The bulletin of mathematical biophysics 5(4), 115–133 (1943) https: //doi.org/10.1007/bf02478259

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This paper cites The Journal of physiology 148(3), 574 (1959) https://doi.org/10.1113/ jphysiol.1959.sp006308.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks The Journal of physiology 148(3), 574 (1959) https://doi.org/10.1113/ jphysiol.1959.sp006308

Reference 3

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This paper cites Proceedings of the IEEE 86(11), 2278–2324 (1998) https: //doi.org/10.1109/5.726791.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Proceedings of the IEEE 86(11), 2278–2324 (1998) https: //doi.org/10.1109/5.726791

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This paper cites nature 521(7553), 436–444 (2015) https://doi.org/10.1145/3355047.3359415.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks nature 521(7553), 436–444 (2015) https://doi.org/10.1145/3355047.3359415

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This paper cites : Coupling visual semantics of artiﬁcial neural networks and human brain function via synchronized activations.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks : Coupling visual semantics of artiﬁcial neural networks and human brain function via synchronized activations

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This paper cites In: Proceedings of the AAAI Conference on Artiﬁcial Intelligence, vol.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks In: Proceedings of the AAAI Conference on Artiﬁcial Intelligence, vol

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This paper cites Nature Machine Intelligence 6(12), 1467–1477 (2024) https://doi.org/10.1038/ s42256-024-00925-4.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Nature Machine Intelligence 6(12), 1467–1477 (2024) https://doi.org/10.1038/ s42256-024-00925-4

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This paper cites In: Advances in Neural Information Processing S ystems (2025).

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks In: Advances in Neural Information Processing S ystems (2025)

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This paper cites Nature Machine Intelligence, 1–15 (2025) https://doi.org/10.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Nature Machine Intelligence, 1–15 (2025) https://doi.org/10

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This paper cites Nature computational science, 1–11 (2025) https://doi.org/10.1038/s43588-025-00863-0.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Nature computational science, 1–11 (2025) https://doi.org/10.1038/s43588-025-00863-0

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This paper cites Nature human behaviour, 1–15 (2025) https://doi.org/10.1038/s41562-025-02105-9.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Nature human behaviour, 1–15 (2025) https://doi.org/10.1038/s41562-025-02105-9

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This paper cites Nature Machine Intelligence, 1–16 (2025) https://doi.org/10.1038/s42256-025-01049-z.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Nature Machine Intelligence, 1–16 (2025) https://doi.org/10.1038/s42256-025-01049-z

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This paper cites How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

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This paper cites In: Eu ropean Conference on Computer Vision, pp.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks In: Eu ropean Conference on Computer Vision, pp

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This paper cites Science Advanc es 10(39) (2024) https://doi.org/10.1126/sciadv.adl1776.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Science Advanc es 10(39) (2024) https://doi.org/10.1126/sciadv.adl1776

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This paper cites Proceedings of the National Academy of Sciences 118(3) (2021) https://doi.org/ 10.1073/pnas.2014196118.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Proceedings of the National Academy of Sciences 118(3) (2021) https://doi.org/ 10.1073/pnas.2014196118

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This paper cites Nature Communications 13(1) (2022) https://doi.org/10.1038/s41467-022-28091-4.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Nature Communications 13(1) (2022) https://doi.org/10.1038/s41467-022-28091-4

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This paper cites Disentangling the Factors of Convergence between Brains and Computer Vision Models.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Disentangling the Factors of Convergence between Brains and Computer Vision Models

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks In: Proceedings 27 of the IEEE/CVF International Conference on Computer Vision, pp

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks BEiT: BERT Pre-Training of Image Transformers

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks DINOv2: Learning Robust Visual Features without Supervision

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks In: Proceedings of the IEEE/CVF Conferen ce on Computer Vision and Pattern Recognition, pp

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks OpenAI Blog

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Learning Transferable Visual Models From Natural Language Supervision

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Are we done with ImageNet?

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks From Colors to Classes: Emergence of Concepts in Vision Transformers

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Dissecting Query-Key Interaction in Vision Transformers

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Emergent Abilities of Large Language Models

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Instruction-tuning Aligns LLMs to the Human Brain

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Better artificial intelligence does not mean better models of biology

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks What Are Large Language Models Mapping to in the Brain? A Case Against Over-Reliance on Brain Scores

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Neuron 95(2), 245–258 (2017) https://doi.org/10

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks : The wu-minn human connectome project: an overview

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks : Increasing diversity in connectomics with the chinese human connectome project

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks : The minimal preprocessing pipelines for the human connectome project

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Psychoradiology 1(1), 23–41 (2021) https://doi.org/10.1093/psyrad/ kkab002

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks : The organiza- tion of the human cerebral cortex estimated by intrinsic functional c onnectivity

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks , Ramachandran, S.C., Pisner, D.A., Frank, P.F., Lemmer, A.D., Nikolaidis, A., Vogelst ein, J.T.: Standardizing human brain parcellations

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Neuroimage 237, 118164 (2021) https: //doi.org/10.1016/j.neuroimage.2021.118164

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A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks 3-Augment

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