Does Learning Protein Folding Generalize to Broader Reasoning?
This paper investigates whether learning to predict protein structures can help improve general reasoning in large language models, and the results show that it can lead to better performance on a range of tasks, from spatial reasoning to scientific and general reasoning. Practitioners may care about this because it suggests that using non-linguistic data to fine-tune language models can improve their ability to reason and make more accurate predictions.