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Found 2 papers, 1 papers with code
FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives
AI models (including LLM) often rely on narrative question-answering (QA) datasets to provide customized QA functionalities to support downstream children education applications; however, existing datasets only include QA pairs that are grounded within the given storybook content, but children can learn more when teachers refer the storybook content to real-world knowledge (e. g., commonsense knowledge).
An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings Learning
To address this problem, we present an information minimization based contrastive learning (InforMin-CL) model to retain the useful information and discard the redundant information by maximizing the mutual information and minimizing the information entropy between positive instances meanwhile for unsupervised sentence representation learning.
