93 citations · 93 across the 7 of their papers we have counts for
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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.LG2026
Certified but Private: Scalable Zero-Knowledge Proofs for Neural Network Guarantees
Youwei Zhong, Ben Merbaum, Timos Antonopoulos +4
With the growing deployment of machine learning models, formal guarantees of the robustness and fairness of these models have become increasingly important in safety-critical and l…
cs.DS2026
On a Conjecture for Parameterized st-Orientations
Charalampos Papamanthou
MaxSTN and MinSTN -- proposed by Papamanthou and Tollis (TCS 2008, JGAA 2010) -- are two algorithms for producing -orientations of biconnected graphs with long and short longes…