AI Research
Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices
Bridging neural language models with symbolic logic for robust computation on resource-constrained hardware.
Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on such devices are unreliable on the tasks computers are expected to handle well, such as arithmetic, algebra, and formal logic pr...
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ArXiv CS.AI
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ArXiv CS.AI
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Neurosymbolic routing bridges the gap between deep learning intuition and deterministic logic, enabling reliable reasoning on small-scale devices. By offloading complex tasks to symbolic solvers, this method allows edge hardware to achieve accuracy levels previously reserved for massive cloud models.
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