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data selection

250 papers

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Co-occurring keywords · papers mentioning both

domain adaptation (43) large language model (42) neural machine translation (38) instruction tuning (28) language model (26) transfer learning (23) active learning (20) curriculum learning (18) automatic speech recognition (12) self-supervised learning (11)

Papers

CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning NeurIPS 2024 CLUES: Collaborative Private-domain High-quality Data Selection for LLMs via Training Dynamics NeurIPS 2024 Clustering and Ranking: Diversity-preserved Instruction Selection through Expert-aligned Quality Estimation EMNLP 2024 CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training NeurIPS 2024 Concept-skill Transferability-based Data Selection for Large Vision-Language Models EMNLP 2024 Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity AISTATS 2024 Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning ACL 2024 Deep Active Learning with Noise Stability AAAI 2024 Domain-Aware Data Selection for Speech Classification via Meta-Reweighting Interspeech 2024 Efficient Continual Pre-training for Building Domain Specific Large Language Models ACL 2024 From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning NAACL 2024 G-DIG: Towards Gradient-based DIverse and hiGh-quality Instruction Data Selection for Machine Translation ACL 2024 Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs ICLR 2024 GREATS: Online Selection of High-Quality Data for LLM Training in Every Iteration NeurIPS 2024 IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models ICLR 2024 Improving Subgroup Robustness via Data Selection NeurIPS 2024 MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models NeurIPS 2024 One-Shot Learning as Instruction Data Prospector for Large Language Models ACL 2024 Reliable Data Generation and Selection for Low-Resource Relation Extraction AAAI 2024 Robust Guidance for Unsupervised Data Selection: Capturing Perplexing Named Entities for Domain-Specific Machine Translation COLING 2024 SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection NeurIPS 2024 Sequence Reducible Holdout Loss for Language Model Pretraining COLING 2024 SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning NeurIPS 2024 Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning NeurIPS 2024 SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models NeurIPS 2024