A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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This paper explores uncertainty quantification for black-box large language models in natural language generation, addressing a previously under-explored problem.
M. Greenwell Brandon
This paper introduces pdp, an R package for constructing partial dependence plots to explain black-box machine learning models.
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A technical review of meta-learning methods, categorizing them into black-box, optimization-based, and other approaches, and discussing advances and challenges.
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SelfCheckGPT is a zero-resource, black-box hallucination detection method for generative LLMs that uses sampling-based consistency checking.
Jiawei Su, Danilo Vasconcellos Vargas, Kouichi Sakurai
Proposes a black-box one-pixel attack using differential evolution that fools DNNs by modifying a single pixel, achieving 67.97% success on CIFAR-10.
Vikas Hassija, Vinay Chamola, Atmesh Mahapatra, et al.
A comprehensive review of explainable AI (XAI) methods for interpreting black-box models, covering frameworks, efficacy, and emerging issues.