data pruning

Batch Loss Score for Dynamic Data Pruning CVPR 2026 Investigating Data Pruning for Pretraining Biological Foundation Models at Scale AAAI 2026 Language Model-Driven Data Pruning Enables Efficient Active Learning EACL 2026 LoPrune: Efficient Data Pruning for LoRA-Based Fine-Tuning of Vision Transformer CVPR 2026 Data Pruning by Information Maximization ICLR 2025 Disentangling the Roles of Representation and Selection in Data Pruning ACL 2025 DRoP: Distributionally Robust Data Pruning ICLR 2025 Enhancing Training Data Quality through Influence Scores for Generalizable Classification: A Case Study on Sexism Detection IJCNLP 2025 Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory ICLR 2025 Partial Forward Blocking: A Novel Data Pruning Paradigm for Lossless Training Acceleration ICCV 2025 Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models ICLR 2025 Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation ICLR 2025 Scale Efficient Training for Large Datasets CVPR 2025 Severing Spurious Correlations with Data Pruning ICLR 2025 D^2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning ICLR 2024 Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization NeurIPS 2024 BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges ICML 2024 Critical Learning Periods: Leveraging Early Training Dynamics for Efficient Data Pruning ACL 2024 Dynamic Data Pruning for Automatic Speech Recognition Interspeech 2024 GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning NeurIPS 2024 HEPrune: Fast Private Training of Deep Neural Networks With Encrypted Data Pruning NeurIPS 2024 How Do Your Code LLMs perform? Empowering Code Instruction Tuning with Really Good Data EMNLP 2024 InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning ICLR 2024 Mind the Boundary: Coreset Selection via Reconstructing the Decision Boundary ICML 2024 Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning ICLR 2024