4 papers
Minions: A Dynamic and Distributed Virtual GPU Cloud Built on Idle Apple Silicon Devices
Jianhua Li, Yun Xing, Girisha De Silva +3
The increasing demand for GPU-accelerated machine learning inference has exposed limitations in centralized GPU infrastructures, including high cost, limited elasticity, and long w…
Adaptive Model Compression (AMC): Saliency-Driven Resource Allocation for Ultra-Low-Power Transformer Inference
Jiayin Hu, Kai Yuan, Vanessa Hu +3
Deploying large-scale transformer models on resource-constrained edge devices remains a challenge due to the high energy and memory overhead inherent in static inference, which pro…
Unifying Ranking and Generation in Query Auto-Completion via Retrieval-Augmented Generation and Multi-Objective Alignment
Kai Yuan, Anthony Zheng, Jia Hu +9
Query Auto-Completion (QAC) suggests query completions as users type, helping them articulate intent and reach results more efficiently. Existing approaches face fundamental challe…
Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments
Evangelia Christakopoulou, Vivekkumar Patel, Hemanth Velaga +3
Large-scale commercial search systems optimize for relevance to drive successful sessions that help users find what they are looking for. To maximize relevance, we leverage two com…