2 citations · 7 across the 10 of their papers we have counts for
10 papers
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…
Efficient Volume Computation for SMT Formulas
Arijit Shaw, Uddalok Sarkar, Kuldeep S. Meel
Satisfiability Modulo Theory (SMT) has recently emerged as a powerful tool for solving various automated reasoning problems across diverse domains. Unlike traditional satisfiabilit…
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…
Assessing the Quality of Binomial Samplers: A Statistical Distance Framework
Uddalok Sarkar, Sourav Chakraborty, Kuldeep S. Meel
Randomized algorithms depend on accurate sampling from probability distributions, as their correctness and performance hinge on the quality of the generated samples. However, even…
Testing Self-Reducible Samplers
Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote +2
Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to fi…
A Fractal Approach to Characterize Emotions in Audio and Visual Domain: A Study on Cross-Modal Interaction
Sayan Nag, Uddalok Sarkar, Shankha Sanyal +5
It is already known that both auditory and visual stimulus is able to convey emotions in human mind to different extent. The strength or intensity of the emotional arousal vary dep…