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National University of Defense Technology
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Forget static layer selection – GRASS dynamically adapts which layers to fine-tune based on gradient norms, unlocking significant memory savings and accuracy gains.
Autonomous exploration by an LLM agent dramatically outperforms both rigid retrieval workflows and supervised fine-tuning for temporal knowledge graph question answering, achieving state-of-the-art results in a zero-shot setting.
