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Looped transformers compute by applying one block repeatedly, so they can run for more loops than they were trained with. Recurrent reasoners are known to overthink: iterating past the trained depth can turn a correct answer into a wrong one. Such a late error can reflect failed computation, loss of retention, or a sta...
CLOSER-Bench is introduced, a controlled evaluation protocol for budgeted cross-stage design closure and a ten-task pilot spanning RTL repair, mutation-based verification, coverage, PPA optimization, design-space exploration, cross-model debugging, and security establishes the executable harness.
RTLCurator is presented, which learns a behavior-aware compatibility prior by contrasting each specification with implementations that fail simulation, and calibrates it to a new corpus using a small number of validated pairs, and constructs the retained subset by balancing alignment, representation coverage, and RTL s...
ChipFuzzer is proposed, a hardware fuzzing framework that leverages the semantic reasoning capabilities of large language models (LLMs) to improve fuzzing effectiveness and improves average condition coverage and bug detection rate over the strongest baseline.
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