Verifiable evaluations of machine learning models using zkSNARKs

5 February 2024

Papers citing "Verifiable evaluations of machine learning models using zkSNARKs"

6 / 6 papers shown

Title
TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks Mohammad Maheri Hamed Haddadi Alex Davidson 63 0 0 27 Apr 2025
Trust the Process: Zero-Knowledge Machine Learning to Enhance Trust in Generative AI Interactions Bianca-Mihaela Ganescu Jonathan Passerat-Palmbach SyDa 33 8 0 09 Feb 2024
FairCompass: Operationalising Fairness in Machine Learning Jessica Liu Huaming Chen Jun Shen Kim-Kwang Raymond Choo FaML 32 5 0 27 Dec 2023
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP Anya Belz Craig Thomson Ehud Reiter Gavin Abercrombie J. Alonso-Moral ... Antonio Toral Xiao-Yi Wan Leo Wanner Lewis J. Watson Diyi Yang 66 35 0 02 May 2023
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,453 0 23 Jan 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,203 0 23 Aug 2019