Even a well-calibrated LLM may struggle to estimate uncertainty during fine-tuning duetocatastrophic forgetting ofgeneral knowledge [84].

Large Language Models (LLMs) have the capacity to store and recall facts.

This challenge necessitates new mathematical and algorithmic tools that enable adaptation and zero-shot transfer.

We build strong baseline models upon large pretrained language models, including GPT -3 and T5. Our benchmark is an ongoing effort, and this paper presents real-time evaluation results over the past year.

The rapid evolution of large language models (LLMs) has expanded their capabilities across various data modalities, extending from well-established image data to increasingly popular graph data.