ImplicitHop: Evaluating knowledge integration across context and memory
The ability to integrate new information and deduce its consequences is central to learning, understanding, and reasoning in large language models (LLMs). Whether information arrives during training or in-context, models must not only store local facts, but propagate their long-range implications globally. To explore information integration in LLMs, we introduce two complementary natural language…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
