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Parameter importance isn't forever: dynamically adapting which parameters are frozen during fine-tuning significantly improves generalization and reduces forgetting in LLMs.
Achieve state-of-the-art results in temporal knowledge graph question answering by explicitly modeling temporal constraints within both question representations and graph reasoning.
