4 papers · 1 filter
Optimal control of the future via prospective learning with control
Yuxin Bai, Aranyak Acharyya, Ashwin De Silva +3
Optimal control of the future is the next frontier for AI. Current approaches to this problem are typically rooted in reinforcement learning (RL). RL is mathematically distinct fro…
Concentration bounds on response-based vector embeddings of black-box generative models
Aranyak Acharyya, Joshua Agterberg, Youngser Park +1
Generative models, such as large language models or text-to-image diffusion models, can generate relevant responses to user-given queries. Response-based vector embeddings of gener…
Testing for LLM response differences: the case of a composite null consisting of semantically irrelevant query perturbations
Aranyak Acharyya, Carey E. Priebe, Hayden S. Helm
Given an input query, generative models such as large language models produce a random response drawn from a response distribution. Given two input queries, it is natural to ask if…
Convergence guarantees for response prediction for latent structure network time series
Aranyak Acharyya, Francesco Sanna Passino, Michael W. Trosset +1
In this article, we propose a technique to predict the response associated with an unlabeled time series of networks in a semisupervised setting. Our model involves a collection of…