A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference
Rising privacy concerns around large language models have accelerated research in private Transformer inference (PTI). Synthesizing the empirical claims in this line of research, however, is hindered by multi-dimensional cryptographic progress and inconsistent evaluation contracts. In this work, we systematize the field by constructing an empirical graph of 62 PTI systems, mapping system attributes to node features and evaluation compatibility to edges. A three-tiered analysis of this graph illuminates the state of private inference. Node-level attribution shows that cryptographic progress drives performance gains across most systems, yet always co-occurs with other factors (model fidelit...
| Authors | Souvik Das, Ariful Azad, Nitesh Saxena |
|---|---|
| Primary category | cs.CR |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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