Multi-Step Knowledge Interaction Analysis via Rank-2 Subspace Disentanglement

arXiv — cs.LG•Tuesday, November 4, 2025 at 5:00:00 AM

A recent study published on arXiv investigates the interaction between Natural Language Explanations (NLEs) and the knowledge embedded within Large Language Models (LLMs). The research emphasizes the significance of understanding how external Context Knowledge and Parametric Knowledge jointly influence model behavior, an area that has been largely neglected in prior work. Previous studies predominantly concentrated on single-step generation processes, overlooking the multi-step dynamics involved in knowledge interaction. By focusing on this multi-step knowledge interaction, the study aims to provide deeper insights into the mechanisms through which LLMs integrate and utilize different types of knowledge during explanation generation. This approach marks a shift from earlier research paradigms and could have implications for improving the interpretability and reliability of LLM outputs. The findings contribute to ongoing efforts in the AI community to better comprehend and enhance the explanatory capabilities of language models.

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