:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gizdov, Andrey, Procopio, Andrea, Li, Yichen, Harari, Daniel, Ullman, Tomer
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	https://arxiv.org/abs/2512.00365
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Human-Like Coarse Object Representations in Vision Models
by: Gizdov, Andrey, et al.
Published: (2026)

Time-Series at the Edge: Tiny Separable CNNs for Wearable Gait Detection and Optimal Sensor Placement
by: Procopio, Andrea, et al.
Published: (2025)

Chain of Time: In-Context Physical Simulation with Image Generation Models
by: Wang, YingQiao, et al.
Published: (2025)

Self-supervised vision-langage alignment of deep learning representations for bone X-rays analysis
by: Englebert, Alexandre, et al.
Published: (2024)

VLA-Mark: A cross modal watermark for large vision-language alignment model
by: Liu, Shuliang, et al.
Published: (2025)

Hallucination-aware intermediate representation edit in large vision-language models
by: Suo, Wei, et al.
Published: (2026)

Improving vision-language alignment with graph spiking hybrid Networks
by: Zhang, Siyu, et al.
Published: (2025)

The Illusion-Illusion: Vision Language Models See Illusions Where There are None
by: Ullman, Tomer
Published: (2024)

AGA: An adaptive group alignment framework for structured medical cross-modal representation learning
by: Li, Wei, et al.
Published: (2025)

Human alignment of neural network representations
by: Muttenthaler, Lukas, et al.
Published: (2022)

Untrained neural networks can demonstrate memorization-independent abstract reasoning
by: Barak, Tomer, et al.
Published: (2024)

Towards a vision foundation model for comprehensive assessment of Cardiac MRI
by: Jacob, Athira J, et al.
Published: (2024)

AdCare-VLM: Towards a Unified and Pre-aligned Latent Representation for Healthcare Video Understanding
by: Jabin, Md Asaduzzaman, et al.
Published: (2025)

Generalizing vision-language models to novel domains: A comprehensive survey
by: Li, Xinyao, et al.
Published: (2025)

Self-supervised video pretraining yields robust and more human-aligned visual representations
by: Parthasarathy, Nikhil, et al.
Published: (2022)

Evaluating alignment between humans and neural network representations in image-based learning tasks
by: Demircan, Can, et al.
Published: (2023)

Are vision language models robust to uncertain inputs?
by: Wang, Xi, et al.
Published: (2025)

PEAR: Pixel-aligned Expressive humAn mesh Recovery
by: Wu, Jiahao, et al.
Published: (2026)

Interpreting vision transformers via residual replacement model
by: Kim, Jinyeong, et al.
Published: (2025)

Quantifying the human visual exposome with vision language models
by: Rominger, Christian, et al.
Published: (2026)

What matters when building vision-language models?
by: Laurençon, Hugo, et al.
Published: (2024)

Action Without Interaction: Probing the Physical Foundations of Video LMMs via Contact-Release Detection
by: Harari, Daniel, et al.
Published: (2025)

Dimensions underlying the representational alignment of deep neural networks with humans
by: Mahner, Florian P., et al.
Published: (2024)

DOGR: Towards Versatile Visual Document Grounding and Referring
by: Zhou, Yinan, et al.
Published: (2024)

Auto-regressive transformation for image alignment
by: Lee, Kanggeon, et al.
Published: (2025)

Thinker: A vision-language foundation model for embodied intelligence
by: Pan, Baiyu, et al.
Published: (2026)

A multimodal vision foundation model for generalizable knee pathology
by: Yu, Kang, et al.
Published: (2026)

RadEdit: stress-testing biomedical vision models via diffusion image editing
by: Pérez-García, Fernando, et al.
Published: (2023)

Self-adaptive vision-language model for 3D segmentation of pulmonary artery and vein
by: Guo, Xiaotong, et al.
Published: (2025)

Phantom: Subject-consistent video generation via cross-modal alignment
by: Liu, Lijie, et al.
Published: (2025)

Building and better understanding vision-language models: insights and future directions
by: Laurençon, Hugo, et al.
Published: (2024)

MMToM-QA: Multimodal Theory of Mind Question Answering
by: Jin, Chuanyang, et al.
Published: (2024)

Towards Self-Improvement of Diffusion Models via Group Preference Optimization
by: Chen, Renjie, et al.
Published: (2025)

Dilated Convolution with Learnable Spacings makes visual models more aligned with humans: a Grad-CAM study
by: Chamas, Rabih, et al.
Published: (2024)

Spread them Apart: Towards Robust Watermarking of Generated Content
by: Pautov, Mikhail, et al.
Published: (2025)

A benchmark multimodal oro-dental dataset for large vision-language models
by: Lv, Haoxin, et al.
Published: (2025)

Addressing a fundamental limitation in deep vision models: lack of spatial attention
by: Borji, Ali
Published: (2024)

Near, far: Patch-ordering enhances vision foundation models' scene understanding
by: Pariza, Valentinos, et al.
Published: (2024)

Representation geometry shapes task performance in vision-language modeling for CT enterography
by: Minoccheri, Cristian, et al.
Published: (2026)

Beyond the Hype: A dispassionate look at vision-language models in medical scenario
by: Nan, Yang, et al.
Published: (2024)