Imagen de Portada

Revisiting Active Learning in the Era of Vision Foundation Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Gupte, Sanket Rajan, Aklilu, Josiah, Nirschl, Jeffrey J., Yeung-Levy, Serena
Formato:	Preprint
Publicado:	2024
Materias:	Computer Vision and Pattern Recognition Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Zero-shot Action Localization via the Confidence of Large Vision-Language Models
por: Aklilu, Josiah, et al.
Publicado: (2024)

Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models
por: Gu, Jeffrey, et al.
Publicado: (2025)

μ-Bench: A Vision-Language Benchmark for Microscopy Understanding
por: Lozano, Alejandro, et al.
Publicado: (2024)

Depth-guided NeRF Training via Earth Mover's Distance
por: Rau, Anita, et al.
Publicado: (2024)

Just Shift It: Test-Time Prototype Shifting for Zero-Shot Generalization with Vision-Language Models
por: Sui, Elaine, et al.
Publicado: (2024)

Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation
por: Zhang, Yuhui, et al.
Publicado: (2025)

The Impact of Image Resolution on Biomedical Multimodal Large Language Models
por: Chen, Liangyu, et al.
Publicado: (2025)

Feather the Throttle: Revisiting Visual Token Pruning for Vision-Language Model Acceleration
por: Endo, Mark, et al.
Publicado: (2024)

Revisiting Model Stitching In the Foundation Model Era
por: Mai, Zheda, et al.
Publicado: (2026)

Systematic Evaluation of Large Vision-Language Models for Surgical Artificial Intelligence
por: Rau, Anita, et al.
Publicado: (2025)

NegVQA: Can Vision Language Models Understand Negation?
por: Zhang, Yuhui, et al.
Publicado: (2025)

V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think
por: Tang, Bingda, et al.
Publicado: (2026)

Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data
por: Zhang, Yuhui, et al.
Publicado: (2024)

Viewpoint Textual Inversion: Discovering Scene Representations and 3D View Control in 2D Diffusion Models
por: Burgess, James, et al.
Publicado: (2023)

Ask, Pose, Unite: Scaling Data Acquisition for Close Interactions with Vision Language Models
por: Bravo-Sánchez, Laura, et al.
Publicado: (2024)

BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature
por: Lozano, Alejandro, et al.
Publicado: (2025)

Fine-tuning MLLMs Without Forgetting Is Easier Than You Think
por: Li, He, et al.
Publicado: (2026)

CellFlux: Simulating Cellular Morphology Changes via Flow Matching
por: Zhang, Yuhui, et al.
Publicado: (2025)

Downscaling Intelligence: Exploring Perception and Reasoning Bottlenecks in Small Multimodal Models
por: Endo, Mark, et al.
Publicado: (2025)

Revisiting Unknowns: Towards Effective and Efficient Open-Set Active Learning
por: Zong, Chen-Chen, et al.
Publicado: (2026)

Foundation Model Makes Clustering A Better Initialization For Cold-Start Active Learning
por: Yuan, Han, et al.
Publicado: (2024)

MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific Research
por: Burgess, James, et al.
Publicado: (2025)

Revisiting Shape from Polarization in the Era of Vision Foundation Models
por: Li, Chenhao, et al.
Publicado: (2026)

Parameter-Efficient Adaptation of Pre-Trained Vision Foundation Models for Active and Passive Seismic Data Denoising
por: Zhao, Jiahua, et al.
Publicado: (2026)

Why are Visually-Grounded Language Models Bad at Image Classification?
por: Zhang, Yuhui, et al.
Publicado: (2024)

LatentGAN Autoencoder: Learning Disentangled Latent Distribution
por: Kalwar, Sanket, et al.
Publicado: (2022)

Vision Foundation Models in Remote Sensing: A Survey
por: Lu, Siqi, et al.
Publicado: (2024)

Active Zero: Self-Evolving Vision-Language Models through Active Environment Exploration
por: He, Jinghan, et al.
Publicado: (2026)

Data or Language Supervision: What Makes CLIP Better than DINO?
por: Liu, Yiming, et al.
Publicado: (2025)

Uncertainty-Aware Image Classification In Biomedical Imaging Using Spectral-normalized Neural Gaussian Processes
por: Meleti, Uma, et al.
Publicado: (2026)

ArtifactLens: Hundreds of Labels Are Enough for Artifact Detection with VLMs
por: Burgess, James, et al.
Publicado: (2026)

Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders
por: Jiang, Yitong, et al.
Publicado: (2026)

Vision Foundation Model Embedding-Based Semantic Anomaly Detection
por: Ronecker, Max Peter, et al.
Publicado: (2025)

Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method
por: Pan, Bikang, et al.
Publicado: (2024)

Hard Cases Detection in Motion Prediction by Vision-Language Foundation Models
por: Yang, Yi, et al.
Publicado: (2024)

Exploring Aleatoric Uncertainty in Object Detection via Vision Foundation Models
por: Cui, Peng, et al.
Publicado: (2024)

VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Vision Backbones
por: Shen, Lefei, et al.
Publicado: (2025)

VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models
por: Bi, Tianci, et al.
Publicado: (2025)

RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models
por: Zhang, Serena, et al.
Publicado: (2024)

Semi-Supervised Fine-Tuning of Vision Foundation Models with Content-Style Decomposition
por: Drozdova, Mariia, et al.
Publicado: (2024)