Recursive Transformers efficiently reuse parameters across model layers, significantly reducing model size with minimal performance loss.

• Introduces layer-wise LoRA for effective parameter sharing in Transformers
• Creates models up to 85% smaller while preserving capabilities
• Enables cheaper deployment of large language models
• Offers a practical approach to reducing computational costs without sacrificing quality

This engineering breakthrough addresses a critical industry challenge: making powerful LLMs more accessible and cost-effective for real-world applications and deployment.

Original Paper: Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA