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

Understand

Natural Language Explanations (NLEs) describe how Large Language Models (LLMs) make decisions by drawing on external Context Knowledge (CK) and Parametric Knowledge (PK).

• Understanding the interaction between these sources is key to assessing NLE grounding, yet these dynamics remain underexplored.
• Prior work has largely focused on i) single-step generation and ii) modeled PK--CK interaction as a binary choice within a rank-1 subspace.
• This approach overlooks richer interactions and how they unfold over longer generations, such as complementary or supportive knowledge.