Update README.md

README.md

@@ -94,14 +94,6 @@ As shown, AstroLLaMA-3-8B-Base_Summary performs competitively, nearly matching t
 
 Notably, the instruct version of this model shows even more significant improvements, highlighting the effectiveness of the summarization approach in capturing and retaining key astronomical concepts. For detailed performance analysis of the instruct version, please refer to Pan et al. 2024.
 
-## Model Limitations and Future Directions
-
-While the summarization approach has shown promising results, there is still room for improvement. Future iterations may benefit from:
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-1. Incorporating a broader range of high-quality astronomical data beyond arXiv, such as textbooks and curated Wikipedia content.
-2. Further refining the summarization process to capture even more relevant information.
-3. Exploring ways to integrate more diverse astronomical concepts and recent discoveries into the training data.
-
 ## Ethical Considerations
 
 While this model is designed for scientific use, users should be mindful of potential misuse, such as generating misleading scientific content. Always verify model outputs against peer-reviewed sources for critical applications.