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No existing LLM architecture can fully bridge the gap in graph inference tasks, with plain GNNs outperforming even the most advanced LLMs in critical areas like community detection.
Achieve centralized-level performance in federated LLM fine-tuning without compromising IP, privacy, or performance on heterogeneous data by using a compressed "proxy" model.
