Imagen de Portada

On the Use of Anchoring for Training Vision Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Narayanaswamy, Vivek, Thopalli, Kowshik, Anirudh, Rushil, Mubarka, Yamen, Sakla, Wesam, Thiagarajan, Jayaraman J.
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Leveraging Registers in Vision Transformers for Robust Adaptation
por: Yellapragada, Srikar, et al.
Publicado: (2025)

Interpretable and Steerable Concept Bottleneck Sparse Autoencoders
por: Kulkarni, Akshay, et al.
Publicado: (2025)

DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation
por: Subramanyam, Rakshith, et al.
Publicado: (2024)

Improving Robustness In Sparse Autoencoders via Masked Regularization
por: Narayanaswamy, Vivek, et al.
Publicado: (2026)

Speeding Up Image Classifiers with Little Companions
por: Liu, Yang, et al.
Publicado: (2024)

`Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning
por: Feinglass, Joshua, et al.
Publicado: (2024)

PAGER: A Framework for Failure Analysis of Deep Regression Models
por: Thiagarajan, Jayaraman J., et al.
Publicado: (2023)

LatentDiff: Scaling Semantic Dataset Comparison to Millions of Images
por: Flora, James, et al.
Publicado: (2026)

Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization
por: Choi, Hongjun, et al.
Publicado: (2024)

ProtAlign: Contrastive learning paradigm for Sequence and structure alignment
por: Ranganath, Aditya, et al.
Publicado: (2026)

Déjà Vu Memorization in Vision-Language Models
por: Jayaraman, Bargav, et al.
Publicado: (2024)

You Never Know: Quantization Induces Inconsistent Biases in Vision-Language Foundation Models
por: Slyman, Eric, et al.
Publicado: (2024)

Training Feature Attribution for Vision Models
por: Bacha, Aziz, et al.
Publicado: (2025)

Train Once, Forget Precisely: Anchored Optimization for Efficient Post-Hoc Unlearning
por: Sanga, Prabhav, et al.
Publicado: (2025)

Towards Long-window Anchoring in Vision-Language Model Distillation
por: Zhou, Haoyi, et al.
Publicado: (2025)

Explaining the Impact of Training on Vision Models via Activation Clustering
por: Boubekki, Ahcène, et al.
Publicado: (2024)

S-E Pipeline: A Vision Transformer (ViT) based Resilient Classification Pipeline for Medical Imaging Against Adversarial Attacks
por: S, Neha A, et al.
Publicado: (2024)

Compositional Adversarial Training for Robust Visual Watermarking
por: Satheesh, Anirudh, et al.
Publicado: (2026)

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models
por: Shi, Junyao, et al.
Publicado: (2024)

VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance
por: Srivastava, Divyansh, et al.
Publicado: (2024)

DARK: Diagonal-Anchored Repulsive Knowledge Distillation for Vision-Language Models under Extreme Compression
por: Saeed, Numan, et al.
Publicado: (2026)

Training a Computer Vision Model for Commercial Bakeries with Primarily Synthetic Images
por: Schmitt, Thomas H., et al.
Publicado: (2024)

Breast Cancer VLMs: Clinically Practical Vision-Language Train-Inference Models
por: Zheng, Shunjie-Fabian, et al.
Publicado: (2025)

Escaping Plato's Cave: JAM for Aligning Independently Trained Vision and Language Models
por: Yoon, Lauren Hyoseo, et al.
Publicado: (2025)

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models
por: Vemulapalli, Raviteja, et al.
Publicado: (2023)

Integrating Edges into U-Net Models with Explainable Activation Maps for Brain Tumor Segmentation using MR Images
por: Sahayam, Subin, et al.
Publicado: (2024)

Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training
por: Zhang, Wenyu, et al.
Publicado: (2024)

Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey and Benchmark
por: Xin, Yi, et al.
Publicado: (2024)

Training-Free Test-Time Adaptation with Brownian Distance Covariance in Vision-Language Models
por: Zhang, Yi, et al.
Publicado: (2026)

Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use
por: Toubal, Imad Eddine, et al.
Publicado: (2024)

Rethinking the Use of Vision Transformers for AI-Generated Image Detection
por: Park, NaHyeon, et al.
Publicado: (2025)

Test-Time Anchoring for Discrete Diffusion Posterior Sampling
por: Rout, Litu, et al.
Publicado: (2025)

Block Selective Reprogramming for On-device Training of Vision Transformers
por: Sarkar, Sreetama, et al.
Publicado: (2024)

HEAL-ViT: Vision Transformers on a spherical mesh for medium-range weather forecasting
por: Ramavajjala, Vivek
Publicado: (2024)

S-GRPO: Unified Post-Training for Large Vision-Language Models
por: Yan, Yuming, et al.
Publicado: (2026)

WebSerial Vision Training for Microcontrollers: A Browser-Based Companion to On-Device CNN Training
por: Ellis, Jeremy
Publicado: (2026)

Measuring Déjà vu Memorization Efficiently
por: Kokhlikyan, Narine, et al.
Publicado: (2025)

RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance
por: Sun, Zhicheng, et al.
Publicado: (2024)

Contrastive Forward-Forward: A Training Algorithm of Vision Transformer
por: Aghagolzadeh, Hossein, et al.
Publicado: (2025)

Inducing Spatial Locality in Vision Transformers through the Training Protocol
por: Toledo, Eduardo Santiago, et al.
Publicado: (2026)