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Enhancing Next-Generation Language Models with Knowledge Graphs: Extending Claude, Mistral IA, and GPT-4 via KG-BERT
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This method proposes a specific architectural integration strategy for incorporating KG-BERT into diverse pre-trained LLMs (Claude, Mistral IA, GPT-4). It involves adding dedicated components such as a KG-dedicated attention layer, modularized cross-layers with lightweight aggregation, or a dedicated attention head. The goal is to enhance the LLMs' factual accuracy, reasoning, and consistency in knowledge-intensive tasks like question answering and entity linking during their inference phase.
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