arXiv Machine Learning
Jun 30
Meta-learning as a principle for human-like visual representations
arXiv:2606. 28399v1 Announce Type: cross Abstract: The structure of human visual representations underpins our capacity for adaptive behaviour.
MAME: Multidimensional Adaptive Metamer Exploration with Human Perceptual Feedback
arXiv:2503. 13212v3 Announce Type: replace Abstract: Alignment between human brain networks and artificial models has become an active research area in vision science and machine learning.
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arXiv AI
Jun 4
Coarse-to-fine Hierarchical Architecture with Sequential Mamba for Brain Reconstruction
arXiv:2606. 04772v1 Announce Type: cross Abstract: Understanding the relationship between deep visual representations and the human visual system is a fundamental challenge in computational neuroscience.
arXiv Computer Vision
Sep 16
Extremely coarse learning objectives induce human-aligned representations in AI vision models
arXiv:2605.05556v2 Announce Type: replace Abstract: Artificial neural networks trained on visual tasks develop internal representations resembling those of the primate visual system, a discovery that...
Hugging Face Trending Papers
Jun 3
Coarse-to-fine Hierarchical Architecture with Sequential Mamba for Brain Reconstruction
Understanding the relationship between deep visual representations and the human visual system is a fundamental challenge in computational neuroscience. While modern vision models achieve strong performance in image recognition, their correspondence with the hierarchical organization of the human visual cortex remains an open question.
arXiv Machine Learning
4d ago
Receptive-field-constrained stimulus optimization for human early and intermediate visual cortex
arXiv:2609.36391v1 Announce Type: cross Abstract: An ongoing challenge in sensory neuroscience is to characterize the feature dimensions encoded by cortical populations. Recent approaches probe featu...
arXiv AI
Jul 7
Human-like Object Grouping in Self-supervised Vision Transformers
arXiv:2603. 13994v2 Announce Type: replace-cross Abstract: Vision foundation models trained with self-supervised objectives achieve strong performance across diverse tasks and exhibit emergent object segmentation properties.
arXiv AI
Jun 2
Versatile Framework with Semantic and Structural guidance for Image Reconstruction from Brain Activity
arXiv:2606. 00121v1 Announce Type: cross Abstract: Reconstructing visual stimuli from brain recordings has been a meaningful and challenging task in brain decoding.
arXiv AI
Jul 17
Parameter-efficient Prompt Tuning of Vision Foundation Model With Adaptive Focal Loss for Interpretable MCI Screening
arXiv:2607. 15047v1 Announce Type: cross Abstract: Mild Cognitive Impairment is a critical early stage of cognitive decline that frequently precedes Alzheimer's disease, yet its automated detection from neuropsychological drawing tests remains fundamentally constrained by data scarcity, class imbalance, and diagnostic ambiguity near clinical boundaries.
arXiv Machine Learning
Jun 5
Vision Hopfield Memory Networks
arXiv:2603. 25157v2 Announce Type: replace Abstract: Recent vision and multimodal foundation backbones, such as Transformer families and state-space models like Mamba, have achieved remarkable progress, enabling unified modeling across images, text, and beyond.
arXiv AI
2d ago
Modeling The Object Representations Underlying Human Physical Reasoning
arXiv:2602.12486v2 Announce Type: replace-cross Abstract: Humans appear to represent objects when reasoning about physics with coarse, volumetric "bodies" that smooth concavities, trading fine visual...
arXiv AI
4d ago
Cross-attention encoding models reveal dynamic spatiotemporal routing across human higher visual cortex
arXiv:2609.36366v1 Announce Type: cross Abstract: Understanding how the brain parses actions and events from time-varying natural inputs is a central challenge in neuroscience. Recent work has used d...
arXiv Computer Vision
6d ago
How Far Can INRs Go? Cross-Domain Parameter-efficient INR-Based Semantic Segmentation for Brain MRI
arXiv:2609.31573v1 Announce Type: new Abstract: Biomedical image segmentation is central to medical image analysis, but practical deployment often faces limited annotations, memory constraints, and c...