coreset selection

SCAN: Bootstrapping Contrastive Pre-training for Data Efficiency ICCV 2025 STAFF: Speculative Coreset Selection for Task-Specific Fine-tuning ICLR 2025 TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data NAACL 2025 D^2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning ICLR 2024 A Training Data Recipe to Accelerate A* Search with Language Models EMNLP 2024 Bayesian Coreset Optimization for Personalized Federated Learning ICLR 2024 Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization NeurIPS 2024 Contributing Dimension Structure of Deep Feature for Coreset Selection AAAI 2024 DEFT-UCS: Data Efficient Fine-Tuning for Pre-Trained Language Models via Unsupervised Core-Set Selection for Text-Editing EMNLP 2024 Dual-Enhanced Coreset Selection with Class-wise Collaboration for Online Blurry Class Incremental Learning CVPR 2024 Feature Distribution Matching by Optimal Transport for Effective and Robust Coreset Selection AAAI 2024 GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning NeurIPS 2024 Gradient Coreset for Federated Learning WACV 2024 In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models EMNLP 2024 Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation NeurIPS 2024 Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary ICML 2024 Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints ICML 2024 Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning ICLR 2024 Spanning Training Progress: Temporal Dual-Depth Scoring (TDDS) for Enhanced Dataset Pruning CVPR 2024 Toward Data Efficient Model Merging between Different Datasets without Performance Degradation ACML 2024 Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm NeurIPS 2023 Coverage-centric Coreset Selection for High Pruning Rates ICLR 2023 Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection NeurIPS 2023 Loss-Curvature Matching for Dataset Selection and Condensation AISTATS 2023 Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning ICLR 2023