arXiv Machine Learning
CipherGenome: Homomorphic Inference for Genomic Mixture-of-Experts
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GenomeOcean Anywhere: Private WebGPU Inference for Genome MoEs
arXiv:2609.35882v1 Announce Type: cross Abstract: Genome foundation models are most useful where sequences are generated, yet the largest models need datacenter accelerators and a place to send priva...
arXiv Machine Learning
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FEnc$^2$: Unifying Data Packing for Efficient Private Inference via Convolution and Architecture-Aware Fragment Encoding
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MOSAIC: Masked Outsourcing of Secure AI Computations
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arXiv AI
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SpliTEE: Improving LLM Inference on Trusted Hardware with Differentially Private GPU Outsourcing
SpliTEE extends the split‑inference architecture of Slalom to large language models by protecting intermediate GPU computations with differential privacy rather than encryption. The authors show that masking intermediate representations is essential, as a prompt‑reconstruction attack can recover prompts with about 80% accuracy. Their global sensitivity analysis bounds the noise needed, and they demonstrate that SpliTEE on Intel TDX achieves near‑double the speed of fully CPU‑based inference and outperforms encryption‑based Slalom while maintaining higher accuracy.
arXiv Machine Learning
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OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design
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