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Found 3 papers, 2 papers with code
How Interpretable are Reasoning Explanations from Prompting Large Language Models?
We present a comprehensive and multifaceted evaluation of interpretability, examining not only faithfulness but also robustness and utility across multiple commonsense reasoning benchmarks.
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal
The increasing use of complex and opaque black box models requires the adoption of interpretable measures, one such option is extractive rationalizing models, which serve as a more interpretable alternative.
A Comprehensive Review on Financial Explainable AI
The success of artificial intelligence (AI), and deep learning models in particular, has led to their widespread adoption across various industries due to their ability to process huge amounts of data and learn complex patterns.
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