Researchers have developed two distinct systems named Coral and CoRAL. Coral is an adaptive system designed for cost-efficient serving of multiple large language models across heterogeneous cloud GPUs, aiming to optimize resource allocation and reduce serving costs by up to 2.79x. CoRAL, on the other hand, is a framework for robotic manipulation that uses LLMs for adaptive control, enabling zero-shot planning by decoupling high-level reasoning from low-level control and improving success rates by over 50% in contact-rich scenarios. AI
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IMPACT Introduces novel approaches for optimizing LLM serving costs and enhancing robotic manipulation capabilities through LLM integration.
RANK_REASON Two distinct research papers are presented, one on LLM serving infrastructure and another on LLM-based robotic control.