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EquivSVA: A Formally Verified Dataset of Behavioral Assertions Across Equivalent RTL Implementations

Paper recorded by Signals 4 on 2026-09-22 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23

Category: cs.LG · 机器学习 · first seen 2026-09-23

Abstract

Large language models are increasingly used to generate SystemVerilog Assertions from natural-language specifica- tions and register-transfer-level designs. Existing datasets and benchmarks support important goals such as large- scale training, formal evaluation, specification-to-assertion generation, and mutation-based testing. A complemen- tary need is to study whether a generated assertion cap-

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#2 most recent of 263 cs.LG papers we have recorded · ↑ newer: A Decentralized Partially Observable Team Decision Methodology with De · ↓ older: Automatic depth-based local center clustering via $β$-integrated local
Cite this page: EquivSVA: A Formally Verified Dataset of Behavioral Assertions Across Equivalent RTL Implementations: the #2 most recent of 263 cs.LG papers we have recorded (as of 2026-09-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/equivsva-a-formally-verified-dataset-of-behavioral-assertions-across-equivalent-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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