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Lyra: A Hardware-Accelerated RISC-V Verification Framework with Generative Model-Based Processor Fuzzing

Paper
First seen 6/10/2026
Last seen 6/10/2026
Evidence 7 chunks

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RELATIONSHIPS

18 connections
DiFuzzRTL compares with → 100% 2e
The paper compares Lyra against DifuzzRTL in empirical evaluations.
Cascade compares with → 100% 2e
The paper compares Lyra against Cascade in empirical evaluations.
RFUZZ mentions → 100% 2e
The paper mentions RFUZZ as a related hardware fuzzing work.
Lyra introduces → 100% 2e
The paper presents Lyra as its primary contribution.
Xinxin Liu authored by → 100% 1e
Xinxin Liu is listed as an author of the paper.
Sa Wang authored by → 100% 1e
Sa Wang is listed as an author of the paper.
Yungang Bao authored by → 100% 1e
Yungang Bao is listed as an author of the paper.
Xitong Gao authored by → 100% 1e
Xitong Gao is listed as an author of the paper.
Kan Shi authored by → 100% 1e
Kan Shi is listed as an author of the paper.
Institute of Computing Technology, Chinese Academy of Sciences authored by → 95% 1e
The paper is affiliated with ICT, CAS.
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences authored by → 95% 1e
The paper is affiliated with SIAT, CAS.
TheHuzz mentions → 100% 1e
The paper mentions TheHuzz as a related hardware fuzzer.
HyperFuzzing mentions → 100% 1e
The paper mentions HyperFuzzing as a related hardware fuzzing work.
GenHuzz mentions → 100% 1e
The paper mentions GenHuzz as a related ML-based fuzzing work.
ProcessorFuzz mentions → 100% 1e
The paper mentions ProcessorFuzz as a related hardware fuzzing tool.
LyraGen introduces → 100% 1e
The paper introduces LyraGen as the domain-specialized generative model component.
Juncheng Huo authored by → 100% 1e
Juncheng Huo is listed as an author of the paper.
Yunfan Gao authored by → 100% 1e
Yunfan Gao is listed as an author of the paper.