claim
Current hybrid approaches for LLM-KG fusion suffer from three core limitations: they introduce semantic noise during context augmentation (Ayoola et al., 2022; Xin et al., 2024), they remain constrained by LLM training biases in candidate generation (Ding Y. et al., 2024), and they create new modality-specific dependencies in multimodal fusion (Liu Q. et al., 2024).

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