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Data selection: at the interface of PDE-based inverse problem and randomized linear algebra
Arxiv
0+阅读 · 10月2日
Train on Validation (ToV): Fast data selection with applications to fine-tuning
Arxiv
0+阅读 · 10月1日
Data Uniformity Improves Training Efficiency and More, with a Convergence Framework Beyond the NTK Regime
Arxiv
0+阅读 · 9月29日
Annotation-Efficient Active Test-Time Adaptation with Conformal Prediction
Arxiv
0+阅读 · 9月30日
Data-Efficient Training by Evolved Sampling
Arxiv
0+阅读 · 9月27日
Teaching LLMs According to Their Aptitude: Adaptive Reasoning for Mathematical Problem Solving
Arxiv
0+阅读 · 7月9日
ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning
Arxiv
0+阅读 · 8月29日
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Arxiv
0+阅读 · 6月5日
LADM: Long-context Training Data Selection with Attention-based Dependency Measurement for LLMs
Arxiv
0+阅读 · 6月25日
A Survey on Data Selection for LLM Instruction Tuning
Arxiv
0+阅读 · 8月26日
A Survey on Data Selection for LLM Instruction Tuning
Arxiv
0+阅读 · 6月23日
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
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