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cs.LG2025
The Energy Cost of Reasoning: Analyzing Energy Usage in LLMs with Test-time Compute
Yunho Jin, Gu-Yeon Wei, David Brooks
Scaling large language models (LLMs) has driven significant advancements, yet it faces diminishing returns and escalating energy demands. This work explores how test-time compute (…
cs.AI2025
FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices
Yuji Chai, Mujin Kwen, Mujin Kwun +2
Deploying LLMs on edge devices presents serious technical challenges. Memory elasticity is crucial for edge devices with unified memory, where memory is shared and fluctuates dynam…