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Found 3 papers, 1 papers with code
Supporting Sensemaking of Large Language Model Outputs at Scale
Large language models (LLMs) are capable of generating multiple responses to a single prompt, yet little effort has been expended to help end-users or system designers make use of this capability.
ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing
Evaluating outputs of large language models (LLMs) is challenging, requiring making -- and making sense of -- many responses.
Accurate, Explainable, and Private Models: Providing Recourse While Minimizing Training Data Leakage
We present two novel methods to generate differentially private recourse: Differentially Private Model (DPM) and Laplace Recourse (LR).
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