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Found 9 papers, 0 papers with code
SpeCrawler: Generating OpenAPI Specifications from API Documentation Using Large Language Models
By creating a standardized format for numerous APIs, SpeCrawler aids in streamlining integration processes within API orchestrating systems and facilitating the incorporation of tools into LLMs.
What's the Plan? Evaluating and Developing Planning-Aware Techniques for LLMs
Planning is a fundamental task in artificial intelligence that involves finding a sequence of actions that achieve a specified goal in a given environment.
Deep Online Learning with Stochastic Constraints
Deep learning models are considered to be state-of-the-art in many offline machine learning tasks.
Nonparametric Online Learning Using Lipschitz Regularized Deep Neural Networks
Deep neural networks are considered to be state of the art models in many offline machine learning tasks.
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
We consider the problem of uncertainty estimation in the context of (non-Bayesian) deep neural classification.
Growth-Optimal Portfolio Selection under CVaR Constraints
Online portfolio selection research has so far focused mainly on minimizing regret defined in terms of wealth growth.
Multi-Objective Non-parametric Sequential Prediction
Recently, an algorithm for dealing with several objective functions in the i. i. d.
Online Learning of Commission Avoidant Portfolio Ensembles
We present a novel online ensemble learning strategy for portfolio selection.
Online Learning of Portfolio Ensembles with Sector Exposure Regularization
We consider online learning of ensembles of portfolio selection algorithms and aim to regularize risk by encouraging diversification with respect to a predefined risk-driven grouping of stocks.
