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Enhancing Multilingual LLM Pretraining with Model-Based Data Selection
Arxiv
0+阅读 · 2月19日
Entropy-Based Data Selection for Language Models
Arxiv
0+阅读 · 2月19日
ScalSelect: Scalable Training-Free Multimodal Data Selection for Efficient Visual Instruction Tuning
Arxiv
0+阅读 · 2月12日
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Arxiv
0+阅读 · 2月16日
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
Arxiv
0+阅读 · 2月7日
Truth in the Few: High-Value Data Selection for Efficient Multi-Modal Reasoning
Arxiv
0+阅读 · 2月12日
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
Arxiv
0+阅读 · 2月7日
PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery
Arxiv
0+阅读 · 2月12日
Less is More: Improving LLM Alignment via Preference Data Selection
Arxiv
0+阅读 · 2月15日
Pool-based Active Learning as Noisy Lossy Compression: Characterizing Label Complexity via Finite Blocklength Analysis
Arxiv
0+阅读 · 2月5日
OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
Arxiv
0+阅读 · 2月5日
MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
Arxiv
0+阅读 · 2月4日
InstructDiff: Domain-Adaptive Data Selection via Differential Entropy for Efficient LLM Fine-Tuning
Arxiv
0+阅读 · 1月30日
Diverse, not Short: A Length-Controlled Data Selection Strategy for Improving Response Diversity of Language Models
Arxiv
0+阅读 · 1月30日
Action Shapley: A Training Data Selection Metric for World Model in Reinforcement Learning
Arxiv
0+阅读 · 1月15日
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