2 citations · 4 across the 12 of their papers we have counts for
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cs.SD2023★ 1 cited
In-Context Prompt Editing For Conditional Audio Generation
Ernie Chang, Pin-Jie Lin, Yang Li +6
Distributional shift is a central challenge in the deployment of machine learning models as they can be ill-equipped for real-world data. This is particularly evident in text-to-au…
cs.LG2023★ 2 cited
Folding Attention: Memory and Power Optimization for On-Device Transformer-based Streaming Speech Recognition
Yang Li, Liangzhen Lai, Yuan Shangguan +5
Transformer-based models excel in speech recognition. Existing efforts to optimize Transformer inference, typically for long-context applications, center on simplifying attention s…
cs.CR2023★ 1 cited
GPU-based Private Information Retrieval for On-Device Machine Learning Inference
Maximilian Lam, Jeff Johnson, Wenjie Xiong +11
On-device machine learning (ML) inference can enable the use of private user data on user devices without revealing them to remote servers. However, a pure on-device solution to pr…