INK-USC/SalKG

This is the official PyTorch implementation of our NeurIPS 2021 paper: "SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning"

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This project helps researchers and AI practitioners enhance the ability of AI models to answer complex, commonsense questions. By feeding in knowledge graphs and question-answer datasets, it improves how AI models understand and reason about everyday situations. This is ideal for those developing advanced AI systems that need to explain their reasoning.

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Use this if you are a researcher or AI engineer working on natural language understanding and want to improve your models' ability to answer commonsense questions by leveraging knowledge graph explanations.

Not ideal if you need a plug-and-play solution for general natural language processing tasks or do not have access to structured knowledge graph data.

commonsense-reasoning knowledge-graphs natural-language-understanding explainable-ai question-answering
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Python

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Last pushed

Jun 09, 2022

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