1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CR2025
ZKTorch: Compiling ML Inference to Zero-Knowledge Proofs via Parallel Proof Accumulation
Bing-Jyue Chen, Lilia Tang, Daniel Kang
As AI models become ubiquitous in our daily lives, there has been an increasing demand for transparency in ML services. However, the model owner does not want to reveal the weights…
cs.CR2024★ 1 cited
Trustless Audits without Revealing Data or Models
Suppakit Waiwitlikhit, Ion Stoica, Yi Sun +2
There is an increasing conflict between business incentives to hide models and data as trade secrets, and the societal need for algorithmic transparency. For example, a rightsholde…