self-orchestrating-llms

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arXiv Paper Proposes Self-Orchestrating LLMs to Cut Inference Latency

A new arXiv preprint introduces a method for having language models coordinate their own computation by exploiting semantic dependencies between generated tokens. The authors argue that standard autoregressive decoding is slow and leaves GPUs underused when batch sizes are small, and that their approach improves inference efficiency. The work is currently a research preprint and has not been peer reviewed or released as a product.

research/inference/efficiency/llm