Internal Numeracy

Internal numeracy in language models focuses on enabling AI systems to understand and manipulate numerical information within natural language contexts. Current research investigates how to improve numerical reasoning in models like BERT, RoBERTa, and large language models (LLMs) through techniques such as pre-training with calculator usage, semantically priming numerals, and developing novel pretraining objectives that explicitly target numerical understanding. These advancements are significant because improved numerical reasoning capabilities in language models are crucial for applications requiring quantitative analysis within natural language processing tasks, such as financial analysis, scientific literature processing, and educational tools.