Nowadays LLMs are used a lot in reasoning. When we use them in regular tasks (more specifically: those that are covered in the model's training data), it's fine. However, using the models with new information, new rules, and new capabilities would require more caution. 5/n. n=5

Can LLMs reason? When the problems are grounded in the real world, the performance is good. Otherwise, there's a huge performance drop. 4/n

These are common properties for formal reasoning datasets, but have been very hard to incorporate in commonsense reasoning (which is usually considered a type of informal reasoning). 3/n

ACCORD allows (1) controllable reasoning path length, (2) controllable distraction items on the reasoning tree. These controls are (3) automatic and (4) scalable. 2/n