Cover Image

The Easy Path to Robustness: Coreset Selection using Sample Hardness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ramesh, Pranav, Roy, Arjun, Ravikumar, Deepak, Roy, Kaushik, Srinivasan, Gopalakrishnan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Advancing Compressed Video Action Recognition through Progressive Knowledge Distillation
by: Soufleri, Efstathia, et al.
Published: (2024)

Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
by: Alwis, Praditha, et al.
Published: (2026)

DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
by: Roy, Arjun, et al.
Published: (2024)

The Impact of Coreset Selection on Spurious Correlations and Group Robustness
by: Dharmasiri, Amaya, et al.
Published: (2025)

Coresets from Trajectories: Selecting Data via Correlation of Loss Differences
by: Nagaraj, Manish, et al.
Published: (2025)

A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances
by: Moser, Brian B., et al.
Published: (2025)

Coreset Selection for Object Detection
by: Lee, Hojun, et al.
Published: (2024)

SlimDiff: Training-Free, Activation-Guided Hands-free Slimming of Diffusion Models
by: Roy, Arani, et al.
Published: (2025)

Easy to Learn, Yet Hard to Forget: Towards Robust Unlearning Under Bias
by: Kwon, JuneHyoung, et al.
Published: (2026)

Efficient and Robust Quantization-aware Training via Adaptive Coreset Selection
by: Huang, Xijie, et al.
Published: (2023)

Feedback Alignment Meets Low-Rank Manifolds: A Structured Recipe for Local Learning
by: Roy, Arani, et al.
Published: (2025)

MAGIC: Multimodal Alignment & Grounding-aware Instruction Coreset for Vision-Language Models
by: Biswas, Shristi Das, et al.
Published: (2026)

Detection of Cyberbullying in GIF using AI
by: Dave, Pal, et al.
Published: (2025)

Forget Less by Learning Together through Concept Consolidation
by: Kaushik, Arjun Ramesh, et al.
Published: (2026)

Forget Less by Learning from Parents Through Hierarchical Relationships
by: Kaushik, Arjun Ramesh, et al.
Published: (2026)

Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation
by: Negi, Shubham, et al.
Published: (2023)

Coreset selection based on Intra-class diversity
by: Ashraf, Imran, et al.
Published: (2025)

Finding the Muses: Identifying Coresets through Loss Trajectories
by: Nagaraj, Manish, et al.
Published: (2025)

Efficient Multi-bit Quantization Network Training via Weight Bias Correction and Bit-wise Coreset Sampling
by: Kim, Jinhee, et al.
Published: (2025)

Deep Unlearning: Fast and Efficient Gradient-free Approach to Class Forgetting
by: Kodge, Sangamesh, et al.
Published: (2023)

Enhancing Quantization-Aware Training on Edge Devices via Relative Entropy Coreset Selection and Cascaded Layer Correction
by: Tong, Yujia, et al.
Published: (2025)

Active Learning for Finely-Categorized Image-Text Retrieval by Selecting Hard Negative Unpaired Samples
by: Jo, Dae Ung, et al.
Published: (2024)

Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning
by: Littwin, Etai, et al.
Published: (2024)

Exploring Fusion Techniques in Multimodal AI-Based Recruitment: Insights from FairCVdb
by: Swati, Swati, et al.
Published: (2024)

TOFFE -- Temporally-binned Object Flow from Events for High-speed and Energy-Efficient Object Detection and Tracking
by: Kosta, Adarsh Kumar, et al.
Published: (2025)

SCOPE: Semantic Coreset with Orthogonal Projection Embeddings for Federated learning
by: Hossen, Md Anwar, et al.
Published: (2026)

DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
by: Zhang, Yunbei, et al.
Published: (2024)

Discrete Langevin-Inspired Posterior Sampling
by: Amballa, Chaitanya, et al.
Published: (2026)

Deep Model Interpretation with Limited Data : A Coreset-based Approach
by: Behzadi-Khormouji, Hamed, et al.
Published: (2024)

Are Sparse Neural Networks Better Hard Sample Learners?
by: Xiao, Qiao, et al.
Published: (2024)

Improving Generalization via Meta-Learning on Hard Samples
by: Jain, Nishant, et al.
Published: (2024)

Bayesian Autoencoder for Medical Anomaly Detection: Uncertainty-Aware Approach for Brain 2 MRI Analysis
by: Roy, Dip
Published: (2025)

An Approach Towards Learning K-means-friendly Deep Latent Representation
by: Roy, Debapriya
Published: (2024)

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation
by: Vepa, Arvind Murari, et al.
Published: (2024)

SelectMix: Enhancing Label Noise Robustness through Targeted Sample Mixing
by: Liu, Qiuhao, et al.
Published: (2025)

Consistency Models Made Easy
by: Geng, Zhengyang, et al.
Published: (2024)

PICS in Pics: Physics Informed Contour Selection for Rapid Image Segmentation
by: Dwivedi, Vikas, et al.
Published: (2023)

GRILL: Restoring Gradient Signal in Ill-Conditioned Layers for More Effective Adversarial Attacks on Autoencoders
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2025)

Ramen: Robust Test-Time Adaptation of Vision-Language Models with Active Sample Selection
by: Bao, Wenxuan, et al.
Published: (2026)

Language Integration in Fine-Tuning Multimodal Large Language Models for Image-Based Regression
by: Jennings, Roy H., et al.
Published: (2025)