wyu97/RACo
Resources for Retrieval Augmentation for Commonsense Reasoning: A Unified Approach. EMNLP 2022.
This project provides resources for researchers and developers working on AI models that need to understand and apply common sense. It takes a corpus of commonsense knowledge and training data, then outputs a model capable of retrieving relevant commonsense information and answering questions. This is for AI/NLP researchers building or evaluating advanced language understanding systems.
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Use this if you are developing AI models that require strong commonsense reasoning capabilities and want to leverage retrieval-augmented approaches.
Not ideal if you are looking for a ready-to-use API or application for general language tasks without deep technical implementation.
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Nov 23, 2022
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