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Found 3 papers, 1 papers with code
Generating Explanations for Cellular Neural Networks
In the real world, higher-order structures are ubiquitous like in molecules or social networks, thus our work significantly enhances the practical applicability of graph explanations.
SaGE: Evaluating Moral Consistency in Large Language Models
To this extent, we construct the Moral Consistency Corpus (MCC), containing 50K moral questions, responses to them by LLMs, and the RoTs that these models followed.
Measuring Moral Inconsistencies in Large Language Models
To address this issue, we propose a novel information-theoretic measure called Semantic Graph Entropy (SGE) to measure the consistency of an LLM in moral scenarios.
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