CASS-RTL identifies correctness-linked attention heads, builds a steering subspace from them, and applies a geometry-aware intervention that raises pass@1/5/10 accuracy 10-20% on VerilogEval and 5% on CVDP across multiple LLMs without retraining or extra labels.
Halueval-wild: Evaluating hallucinations of language models in the wild,
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CASS-RTL: Correctness-Aware Subspace Steering for RTL Generation with LLMs
CASS-RTL identifies correctness-linked attention heads, builds a steering subspace from them, and applies a geometry-aware intervention that raises pass@1/5/10 accuracy 10-20% on VerilogEval and 5% on CVDP across multiple LLMs without retraining or extra labels.