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Found 3 papers, 3 papers with code
PAC Prediction Sets for Large Language Models of Code
Given a trained code generation model, our algorithm leverages a programming language's abstract syntax tree to generate a set of programs such that the correct program is in the set with high-confidence.
Neural Regression For Scale-Varying Targets
In this work, we demonstrate that a major limitation of regression using a mean-squared error loss is its sensitivity to the scale of its targets.
Delta Hedging Liquidity Positions on Automated Market Makers
The dominant measure of loss in a Liquidity Position is Impermanent Loss.
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