From the 1 of 6 linked papers with an AI index.
6 papers
Entropy Equivalence Testing
Clément L. Canonne, Yash Pote, Jonathan Scarlett +1
The paper defines entropy equivalence testing, a relaxation of distribution closeness testing that distinguishes identical distributions from those whose Shannon entropies differ b…
A Distribution Testing Approach to Clustering Distributions
Gunjan Kumar, Yash Pote, Jonathan Scarlett
We study the following distribution clustering problem: Given a hidden partition of distributions into two groups, such that the distributions within each group are the same, a…
Instance Dependent Testing of Samplers using Interval Conditioning
Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2
Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Pro…
Distance Estimation for High-Dimensional Discrete Distributions
Gunjan Kumar, Kuldeep S. Meel, Yash Pote
Given two distributions and over a high-dimensional domain , and a parameter , the goal of distance estimation is to determine t…
Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach
Clément L. Canonne, Yash Pote, Uddalok Sarkar
A growing fraction of all code is sampled from Large Language Models (LLMs). We investigate the problem of attributing code generated by language models using hypothesis testing to…
Learning Probabilistic Temporal Logic Specifications for Stochastic Systems
Rajarshi Roy, Yash Pote, David Parker +1
There has been substantial progress in the inference of formal behavioural specifications from sample trajectories, for example, using Linear Temporal Logic (LTL). However, these t…