Pith Number

pith:VV6ZO7CA

pith:2026:VV6ZO7CAHAGPGER476ZT4MZ3UC

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Characterizing Universal Object Representations Across Vision Models

Florian P. Mahner, Francisco Pereira, Johannes Roth, Ka Chun Lam, Martin N. Hebart, Michael F. Bonner

Vision models converge on universal object dimensions that are more interpretable and align better with biological vision.

arxiv:2605.13675 v1 · 2026-05-13 · cs.CV · cs.LG · q-bio.NC

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Claims

C1strongest claim

In contrast to model-specific dimensions, universal dimensions are more interpretable and more strongly driven by conceptual image properties... models with more universal dimensions also better predict macaque IT activity and human similarity judgments, suggesting that universality reflects representations relevant to biological vision.

C2weakest assumption

That reappearance frequency across the 162 models reliably identifies universal dimensions and that the non-negative decomposition fully captures the relevant object similarity structure without significant loss of information.

C3one line summary

Vision models converge on universal object dimensions that are semantically interpretable and align more closely with biological vision than model-specific ones.

References

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[1] Y . LeCun, Y . Bengio, and G. Hinton. Deep learning.Nature, 521:436–444, 2015 2015

[2] N. Kanwisher, M. Khosla, and K. Dobs. Using artificial neural networks to ask ’why’ questions of minds and brains.Trends in Neurosciences, 46:240–254, 2023 2023

[3] A. Doerig, R. P. Sommers, K. Seeliger, B. Richards, J. Ismael, G. W. Lindsay, K. P. Kording, T. Konkle, M. A. J. van Gerven, N. Kriegeskorte, and T. C. Kietzmann. The neuroconnectionist research progr 2023

[4] D. L. K. Yamins and J. J. DiCarlo. Using goal-driven deep learning models to understand sensory cortex. Nature Neuroscience, 19:356–365, 2016 2016

[5] M. Huh, B. Cheung, T. Wang, and P. Isola. Position: The platonic representation hypothesis.Proceedings of Machine Learning Research, 235:20617–20642, 2024 2024

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Cited by

1 paper in Pith

Receipt and verification

First computed	2026-05-18T02:44:17.112127Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ad7d977c40380cf3123cffb33e333ba08aa22105a61901a6abdc251e16968480

Aliases

arxiv: 2605.13675 · arxiv_version: 2605.13675v1 · doi: 10.48550/arxiv.2605.13675 · pith_short_12: VV6ZO7CAHAGP · pith_short_16: VV6ZO7CAHAGPGER4 · pith_short_8: VV6ZO7CA

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/VV6ZO7CAHAGPGER476ZT4MZ3UC \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ad7d977c40380cf3123cffb33e333ba08aa22105a61901a6abdc251e16968480

Canonical record JSON

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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T15:34:41Z",
    "title_canon_sha256": "1e2f0e11f256be3fad11a3981774c2c565bd502d9034ab45f85a08f61e45285f"
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