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Learning-to-Transition for Large-scale and High-Order MIMO Detection

High-order multiple-input multiple-output (MIMO) detection requires efficient search over a large discrete symbol space while producing reliable soft information for channel decoding. This paper develops a learning-to-transition (L2T) framework that formulates MIMO detection as a stochastic sequence of complete-vector transitions. At each transition, a channel-coupled Transformer updates both the…

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Using RLM Cut's Token Costs by 96% for LLM

As someone who is constantly exploring ways to make AI applications faster and cheaper, I found myself looking for a solution to a problem that kept slowing me down: processing 100,000+ token context…

  • Developer rewrote RLM code in Rust, achieving 37.6% faster execution
  • RLM-Rust implementation reduced token costs by 96.1% for 120,000 tokens
  • Rust-based solution enables efficient processing of large context windows

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