LLMs achieve 98.22% accuracy answering factual questions about ROS2 software architectures, with top models reaching 100%.
Large language models for unit testing: A systematic literature review
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
zkCraft combines LLM-guided mutations with R1CS-aware localization and Violation IOP proofs to detect under- and over-constrained faults in zero-knowledge circuits while reducing solver queries.
citing papers explorer
-
Can Large Language Models Assist the Comprehension of ROS2 Software Architectures?
LLMs achieve 98.22% accuracy answering factual questions about ROS2 software architectures, with top models reaching 100%.
-
zkCraft: Prompt-Guided LLM as a Zero-Shot Mutation Pattern Oracle for TCCT-Powered ZK Fuzzing
zkCraft combines LLM-guided mutations with R1CS-aware localization and Violation IOP proofs to detect under- and over-constrained faults in zero-knowledge circuits while reducing solver queries.