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Diversity-driven Data Selection for Language Model Tuning through Sparse Autoencoder
Arxiv
0+阅读 · 3月31日
Efficient Data Selection for Training Genomic Perturbation Models
Arxiv
0+阅读 · 3月28日
Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging -- An Open Recipe
Arxiv
0+阅读 · 3月27日
D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning
Arxiv
0+阅读 · 3月14日
Adapt-$\infty$: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection
Arxiv
0+阅读 · 3月24日
SelectFormer: Private and Practical Data Selection for Transformers
Arxiv
0+阅读 · 3月1日
Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric
Arxiv
0+阅读 · 2月28日
LADM: Long-context Training Data Selection with Attention-based Dependency Measurement for LLMs
Arxiv
0+阅读 · 3月4日
MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models
Arxiv
0+阅读 · 3月19日
Semi-Supervised In-Context Learning: A Baseline Study
Arxiv
0+阅读 · 3月4日
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Arxiv
0+阅读 · 3月4日
DELIFT: Data Efficient Language model Instruction Fine Tuning
Arxiv
0+阅读 · 3月20日
Picking the Cream of the Crop: Visual-Centric Data Selection with Collaborative Agents
Arxiv
0+阅读 · 2月27日
Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric
Arxiv
0+阅读 · 2月27日
CritiQ: Mining Data Quality Criteria from Human Preferences
Arxiv
0+阅读 · 2月26日
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