HAVEN combines LLM agents for planning and gap analysis with protocol-specific templates and a custom DSL to generate correct UVM testbenches, achieving 100% compilation success, 90.6% code coverage, and 87.9% functional coverage on 19 open-source designs across three protocols.
Grammar prompting for domain-specific language generation with large language models
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
RedParrot accelerates NL-to-DSL conversion by 3.6x with 8.26% accuracy gain on enterprise data and 34.8% on benchmarks via semantic caching of query skeletons and contrastive learning.
citing papers explorer
-
HAVEN: Hybrid Automated Verification ENgine for UVM Testbench Synthesis with LLMs
HAVEN combines LLM agents for planning and gap analysis with protocol-specific templates and a custom DSL to generate correct UVM testbenches, achieving 100% compilation success, 90.6% code coverage, and 87.9% functional coverage on 19 open-source designs across three protocols.
-
RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching
RedParrot accelerates NL-to-DSL conversion by 3.6x with 8.26% accuracy gain on enterprise data and 34.8% on benchmarks via semantic caching of query skeletons and contrastive learning.