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Greetings from GEM Space, the heart of innovation behind our upcoming paper, "FRAGILE MASTERY: ARE DOMAIN-SPECIFIC TRADE-OFFS UNDERMINING ON-DEVICE LANGUAGE MODELS?". We’re thrilled to invite you into our world of edge AI exploration! This repository, GEM_Testing_Arsenal, is a cornerstone of our efforts to redefine On-Device Language Models (ODLMs) through the Generalized Edge Model (GEM). Keep an eye out for the paper link once it’s published!
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## About Our Paper
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***Abstract***
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The deployment of On-Device Language Models (ODLMs) on resource-constrained edge devices demands a delicate balance of efficiency, memory, power, and linguistic skill across diverse tasks. In "FRAGILE MASTERY", we explore the trade-offs between domain-specific optimization and cross-domain robustness, introducing the Generalized Edge Model (GEM). GEM integrates specialization and generalization using a Sparse Cross-Attention Router (SCAR), achieving a cross-domain F1 score of 0.89 with sub-100ms latency on platforms like Raspberry Pi 4 and Pixel 6. Across 47 benchmarks spanning eight domains—healthcare, legal, finance, STEM, and more—GEM boosts general-task performance by 7% over GPT-4 Lite while matching domain-specific results. With new metrics like the Domain Specialization Index (DSI) and a balanced distillation framework cutting catastrophic forgetting by 43%, this work offers a robust foundation for edge AI. [Paper link coming soon!]
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***Our Vision
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At GEM Space, we’re on a mission to revolutionize edge intelligence. We’re striving to build On-Device Language Models that:
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- **Thrive Under Constraints**: Deliver exceptional accuracy and speed on low-power devices—from smartphones to custom NPUs—without compromise.
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- **Master the Balance**: Seamlessly blend domain-specific expertise (think healthcare diagnostics or financial analysis) with robust, cross-domain adaptability.
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- **Empower the Edge**: Bring advanced AI to the fingertips of real-world applications, making it fast, practical, and accessible wherever it’s needed.
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The **GEM_Testing_Arsenal** embodies this ambition—a testing ground for GEM, our pioneering architecture designed to make ODLMs smarter, leaner, and more versatile. We’re here to push the limits of what’s possible and inspire a new era of edge AI innovation.
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# Welcome to GEM Space 🫡
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Greetings from GEM Space, the heart of innovation behind our upcoming paper, "FRAGILE MASTERY: ARE DOMAIN-SPECIFIC TRADE-OFFS UNDERMINING ON-DEVICE LANGUAGE MODELS?". We’re thrilled to invite you into our world of edge AI exploration! This repository, GEM_Testing_Arsenal, is a cornerstone of our efforts to redefine On-Device Language Models (ODLMs) through the Generalized Edge Model (GEM). Keep an eye out for the paper link once it’s published!
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## About Our Paper 📄
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***Abstract***:
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The deployment of On-Device Language Models (ODLMs) on resource-constrained edge devices demands a delicate balance of efficiency, memory, power, and linguistic skill across diverse tasks. In "FRAGILE MASTERY", we explore the trade-offs between domain-specific optimization and cross-domain robustness, introducing the Generalized Edge Model (GEM). GEM integrates specialization and generalization using a Sparse Cross-Attention Router (SCAR), achieving a cross-domain F1 score of 0.89 with sub-100ms latency on platforms like Raspberry Pi 4 and Pixel 6. Across 47 benchmarks spanning eight domains—healthcare, legal, finance, STEM, and more—GEM boosts general-task performance by 7% over GPT-4 Lite while matching domain-specific results. With new metrics like the Domain Specialization Index (DSI) and a balanced distillation framework cutting catastrophic forgetting by 43%, this work offers a robust foundation for edge AI. [Paper link coming soon!]
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***Our Vision***:
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At GEM Space, we’re on a mission to revolutionize edge intelligence. We’re striving to build On-Device Language Models that:
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- **Thrive Under Constraints**: Deliver exceptional accuracy and speed on low-power devices—from smartphones to custom NPUs—without compromise.
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- **Master the Balance**: Seamlessly blend domain-specific expertise (think healthcare diagnostics or financial analysis) with robust, cross-domain adaptability.
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- **Empower the Edge**: Bring advanced AI to the fingertips of real-world applications, making it fast, practical, and accessible wherever it’s needed.
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The **GEM_Testing_Arsenal** embodies this ambition—a testing ground for GEM, our pioneering architecture designed to make ODLMs smarter, leaner, and more versatile. We’re here to push the limits of what’s possible and inspire a new era of edge AI innovation.
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