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Frontier models can be used sparingly for long-horizon tasks by a weak agent that learns to predict when it needs help, then keeps the strong model on a leash.
Quantum LDPC decoding latency plummets by over 13x with a novel GPU-accelerated BP decoder that handles long syndrome histories efficiently.
A compact 1.7B parameter policy can outperform larger models in recommendation tasks by leveraging simulated user feedback for training.