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.
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 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 Machine Learning
Jul 3
Meta-Representational Predictive Coding: Neuroscience-Informed Self-Supervised Learning
arXiv:2503. 21796v2 Announce Type: replace-cross Abstract: Self-supervised learning has become an increasingly important paradigm in the domain of machine intelligence.
arXiv AI
Jul 21
What Makes Linguistic Representations Good Models of High-Level Visual Perception in the Human Brain?
arXiv:2607. 16214v1 Announce Type: cross Abstract: Image descriptions represented with language models (LMs) predict human brain responses to naturalistic images in high-level visual regions, but the factors driving this predictivity remain unclear.
arXiv AI
Jun 16
Harnessing cortical geometry, wiring, and function as inductive biases for recurrent neural networks
arXiv:2606. 14975v1 Announce Type: cross Abstract: How the wiring and functional organization of cortex shape recurrent computation remains a central question in both neuroscience and machine learning.
arXiv Machine Learning
Jun 26
Staying VIGILant: Mitigating Visual Laziness via Counterfactual Visual Alignment in MLLMs
arXiv:2606. 26387v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) extend large language models (LLMs) with visual perception, enabling joint reasoning over images and text.
arXiv AI
Jun 9
Vision Hopfield Memory Networks for Image Recognition
arXiv:2603. 25157v3 Announce Type: replace-cross Abstract: Recent vision backbones, such as Transformer families and state-space models like Mamba, have achieved remarkable progress on image recognition.