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

Observation d8a0e7a7-dea0-4cf5-bdd4-dcf07b5defbf · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:46:44.445179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f0e4b666-9c82-4748-acc9-eda20fe27898 · outbound

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

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.127294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3def4959-ada3-4d5b-89db-1afc54436646 · outbound

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

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T15:46:44.432572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e37f1665-e035-4306-938c-c3ebb2317bd3 · outbound

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

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.144617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24b8b148-ed2a-42cf-8b50-aeaf62c20e0a · outbound

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

Reference 5

Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T15:46:44.344655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ab29953-78d4-4c01-9687-295526bb95eb · outbound

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

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.158459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bdda833-5823-4591-8ea5-133bec881ec2 · outbound

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

Reference 7

Resolution: verified exact; doi, observed 2026-08-15T15:46:43.573586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c0b9131c-36a8-4896-affe-b7acc3678f50 · outbound

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

Reference 8

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T15:46:44.419098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8f49de1-481c-4511-9e74-a552277cf624 · outbound

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)

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-15T15:46:44.212272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b615c01b-7cd9-4a0b-aabd-be1a95d70700 · outbound

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

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:46:44.406190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5d7a3cc1-710b-4f46-8deb-3ddfbfebee8d · outbound

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

Reference 11

Resolution: verified exact; doi, observed 2026-08-15T15:46:43.560555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b17c06d3-05a7-4197-905b-c6e326b90cfe · outbound

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

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.199333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa967802-f7f1-48f9-9118-7584bb3eb698 · outbound

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

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.209969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bb6fed1-a515-4d1c-a276-0ddad4c1184b · outbound

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

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.215936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfda0304-a088-4f7e-b3fe-8b4c4d8eb2cd · outbound

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

Reference 15

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T15:46:44.390999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7059dd52-665a-41c8-9215-63baf2b0cacf · outbound

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

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.228629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a96223a4-97ee-4e1a-bd78-4dd030614364 · outbound

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

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.232694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 226da351-e924-4942-bf53-aa4b4cc66435 · outbound

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

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.237230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 344039ff-31a0-42a1-97c9-5ca847df6425 · outbound

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

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.243166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd5fcf8a-76ac-4093-83ac-09a4d4d82b44 · outbound

This paper cites In: Proceedings 27 of the IEEE/CVF International Conference on Computer Vision, pp.

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

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.247967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07701d86-eb7d-4f17-89d1-d49031ff0363 · outbound

This paper cites BEiT: BERT Pre-Training of Image Transformers.

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

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.253989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2f6188e-66fc-40ef-9fdb-20e8bf4778de · outbound

This paper cites BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers.

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

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.259226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00f704f3-2508-4c59-a7a5-4739b3a49e5f · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

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

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.265562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ae26952-e896-4cb4-82b5-cadf87279421 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conferen ce on Computer Vision and Pattern Recognition, pp.

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

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.271260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75b438fb-77bc-42b1-a2ef-192edec0245b · outbound

This paper cites OpenAI Blog.

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

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:46:44.374186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d7faf362-7b57-4b49-abbc-279617b0c079 · outbound

This paper cites an unresolved cited work.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Unresolved cited work

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.280590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc6b5d8-b872-45fe-a9d8-417d159d4daf · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

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

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.285797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c6fe04-d733-4125-b9a2-cb1e1d278238 · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.

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

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.290470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae89b24a-70b1-4d5d-9e09-4372c38bdf7c · outbound

This paper cites Are we done with ImageNet?.

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

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.294669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff2f4b5a-f823-49c0-9b65-c27bcd4acf36 · outbound

This paper cites an unresolved cited work.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.299761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c394002a-f302-4237-93a9-9ffa25a4289e · outbound

This paper cites From Colors to Classes: Emergence of Concepts in Vision Transformers.

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

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.304293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8452100-59a8-4d20-9cd3-0c3b3f84dda6 · outbound

This paper cites Dissecting Query-Key Interaction in Vision Transformers.

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

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.309458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ed66701-105a-4018-bb61-699be0613bc1 · outbound

This paper cites Emergent Abilities of Large Language Models.

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

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.314033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b385dbce-5485-4293-888f-e3c89423b897 · outbound

This paper cites Instruction-tuning Aligns LLMs to the Human Brain.

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

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.318781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 629c5f1f-9a61-46b5-99ea-7814fce3a478 · outbound

This paper cites an unresolved cited work.

A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.323333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22cc81c5-3441-43b8-9140-ceb16def5de1 · outbound

This paper cites Better artificial intelligence does not mean better models of biology.

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

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.328028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4d6c738-8261-4334-9e73-68a98f305a47 · outbound

This paper cites What Are Large Language Models Mapping to in the Brain? A Case Against Over-Reliance on Brain Scores.

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

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.332795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83b46045-6355-442f-ac6b-a5aca0e6876a · outbound

This paper cites Neuron 95(2), 245–258 (2017) https://doi.org/10.

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

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T15:46:44.359751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d239ef94-36f6-4da0-ab8e-cb630106883c · outbound

This paper cites Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems.

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

Reference 39

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T15:46:43.826460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2af5a17b-d109-44cd-abef-0614af03f40b · outbound

This paper cites : The wu-minn human connectome project: an overview.

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

Reference 40

Resolution: malformed identifier; no resolver link, observed 2026-08-15T15:46:43.347009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f9cd9e7-5129-469a-92d0-9fcf1d95672c · outbound

This paper cites : Increasing diversity in connectomics with the chinese human connectome project.

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

Reference 41

Resolution: verified exact; doi, observed 2026-08-15T15:46:43.472316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d18bfc3b-dc1b-4217-8690-f84a7780651c · outbound

This paper cites : The minimal preprocessing pipelines for the human connectome project.

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

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.356391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ceffbfd-bfc3-46b7-beb1-c4c4cea15c35 · outbound

This paper cites Psychoradiology 1(1), 23–41 (2021) https://doi.org/10.1093/psyrad/ kkab002.

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

Reference 43

Resolution: malformed identifier; doi_truncated, observed 2026-08-15T15:46:43.436704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e1b4d4d0-e4b8-41c4-8e0e-81cfdf3a447d · outbound

This paper cites : The organiza- tion of the human cerebral cortex estimated by intrinsic functional c onnectivity.

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

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.365079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58e60547-01e9-47c7-807d-99a52300e36d · outbound

This paper cites , Ramachandran, S.C., Pisner, D.A., Frank, P.F., Lemmer, A.D., Nikolaidis, A., Vogelst ein, J.T.: Standardizing human brain parcellations.

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

Reference 45

Resolution: verified exact; doi, observed 2026-08-15T15:46:43.421898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0613f329-b9a6-4029-9587-9d198ab26124 · outbound

This paper cites Neuroimage 237, 118164 (2021) https: //doi.org/10.1016/j.neuroimage.2021.118164.

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

Reference 46

Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T15:46:43.738423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2e66e02e-a47b-4e9f-a9a3-a57d95300773 · outbound

This paper cites 3-Augment.

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

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T15:46:43.378229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers