Using interchange interventions on a purpose-built synthetic graph dataset, the paper finds that frozen-LLM features carry node-level information into shallow GNN layers and that an attention-based token and prompt selector adds about 0.7 to 3.1 accuracy points.
Causal feature learning: an overview
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LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
Using interchange interventions on a purpose-built synthetic graph dataset, the paper finds that frozen-LLM features carry node-level information into shallow GNN layers and that an attention-based token and prompt selector adds about 0.7 to 3.1 accuracy points.