LLM Knowledge Editing Benchmarked Using Logical Rules
New research explores pushing the limits of Large Language Model tool calling through experiential knowledge integration and activation. The study, authored by Tatiana Moteu Ngoli, NDah Jean Kouagou, Hamada M. Zahera, and Axel-Cyrille Ngonga Ngomo, addresses the increasing deployment of LLMs in applications requiring accuracy.
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Sources · 7 independent
Modernity/arxiv
“Pushing the Limits of LLM Tool Calling via Experiential Knowledge Integration and Activation.”
Modernity/arxiv
“Benchmarking Knowledge Editing using Logical Rules. Authors: Tatiana Moteu Ngoli, NDah Jean Kouagou, Hamada M. Zahera, Axel-Cyrille Ngonga Ngomo Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications that require a...”
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