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The document presents LLM-JEPA, a novel architecture that integrates Joint Embedding Predictive Architectures (JEPAs) with Large Language Models (LLMs) to enhance their training and performance. LLM-JEPA outperforms traditional LLM training methods across various datasets and models, demonstrating improved generative capabilities while maintaining robustness against overfitting. The proposed method is validated through extensive empirical studies, showing significant benefits in fine-tuning and pretraining

Author

peacefuladv

Language

EN