Abstract: In this paper, we introduce a novel approach for addressing the multi-objective optimization problem in large language model merging via black-box multi-objective optimization algorithms.
With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.
As Enterprise AI matures from experimental chatbots to production-grade Agentic workflows, a silent infrastructure crisis is the VRAM bottleneck. Deploying a dedicated endpoint for every fine-tuned ...
Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...
Abstract: With the explosive growth of users and data-hungry applications, cellular networks are increasingly turning to Autonomous Aerial Vehicles (AAVs) as agile, on-demand aerial base stations. AAV ...
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