![[Experimental] "Temporal LoRA": A dynamic adapter router that switches context (Code vs. Lit) with 100% accuracy. Proof of concept on GPT-2.](https://www.tweakedgeek.com/wp-content/uploads/2026/01/featured-article-8275-300x171.png)
Temporal LoRA introduces a dynamic adapter router that allows models to switch between different contexts, such as coding and literature, with 100% accuracy. By training distinct LoRA adapters for different styles and implementing a "Time Mixer" network, the system can dynamically activate the appropriate adapter based on input context, maintaining model stability while allowing for flexible task switching. This approach provides a promising method for integrating Mixture of Experts (MoE) in larger models without the need for extensive retraining, enabling seamless "hot-swapping" of skills and enhancing multi-tasking capabilities. This matters because it offers a scalable solution for improving AI model adaptability and efficiency in handling diverse tasks.
