Continual Learning meets Generative Modeling Neural networks experience catastrophic forgetting, resulting in a sudden loss of performance on previous tasks when learning new ones. Retraining models from scratch is often impractical due to data size and time constraints. This limitation […]
Garage: Generative-Augmented Retrieval Assisting Generation Enhancement With the recent rise in popularity of generative models (e.g. ChatGPT, GPT4) the issues with the accuracy of the provided information became a great threat. The models might generate a correct answer, but in […]
Garage: Generative-Augmented Retrieval Assisting Generation Enhancement With the recent rise in popularity of generative models (e.g. ChatGPT, GPT4) the issues with the accuracy of the provided information became a great threat. The models might generate a correct answer, but in […]
LongLLaMA – Focused Transformer: Contrastive Training for Context Scaling Large language models can incorporate new information in a contextual manner. However, the full potential of such an approach is often restrained due to a limitation in the effective context length. […]
