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Automating UVM testbench generation with LLMs slashes verification time from days to hours, achieving near-complete code coverage.
Adaptive neural network control plus multi-sensor fusion yields significantly improved trajectory tracking for differential drive robots in the face of unmodeled dynamics and sensor noise.
LLMs can now fix Rust's notoriously tricky undefined behaviors with 92% semantic correctness and 2.2x faster speed, thanks to a novel finite-state machine approach.
