ArticleNature2025
Aligning machine and human visual representations across abstraction levels.
Article in Nature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Systematic image perturbations reveal persistent gaps between human and machine vision.iScience · 2026Article
- Towards robust foundation models for digital pathology.Nature communications · 2026Article
- Article
- Human-like cognitive generalization for large models via mental representation-guided supervision.Nature communications · 2026Article
- AI without representation is just inequity at scale: on the exportation of unrepresentative artificial intelligence models to the Global South.Frontiers in artificial intelligence · 2026Article
- On Benchmarking Human-like Intelligence in Machines.Open mind : discoveries in cognitive science · 2026Article
- Evidence for compositionality in fMRI visual representations via Brain Algebra.Communications biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Deep neural networks have achieved success across a wide range of applications, including as models of human behaviour and neural representations in vision tasks
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.