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cs.CR2026
Maverick: Private and Verifiable LLM Inference Made Practical via Matrix-Vector Multiplication Delegation
Ben Merbaum, Mohammad Amin Raeisi, Wenhao Wang +3
Open-source large language models (LLMs) are increasingly competitive with closed-source models while offering transparency and the ability to run inference without exposing user i…
cs.CR2022★ 1 cited
TRIP: Coercion-resistant Registration for E-Voting with Verifiability and Usability in Votegral
Louis-Henri Merino, Simone Colombo, Rene Reyes +9
Online voting is convenient and flexible, but amplifies the risks of voter coercion and vote buying. One promising mitigation strategy enables voters to give a coercer fake voting…