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Muhammad Abdur Rab Siddiqui

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#machine learning Preprint Sep 2026

Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving

Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajectories extend. While in practice, many queries do not require the capabilities of the largest available model, and routinely directing such queries to a high-capability model...

Muhammad Abdur Rab Siddiqui, Daniel Rojas, Chen Yang et al. · 0 citations