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LLMs struggle to keep up with dynamically changing facts in continual knowledge streams, often exhibiting delays and getting distracted, despite advances in model size and agentic memory systems.
LLMs can be taught to reason more faithfully and accurately by training them to produce reasoning steps that other models can easily follow.