3 papers
cs.SE2025
LLM-as-a-Judge for Reference-less Automatic Code Validation and Refinement for Natural Language to Bash in IT Automation
Ngoc Phuoc An Vo, Brent Paulovicks, Vadim Sheinin
In an effort to automatically evaluate and select the best model and improve code quality for automatic incident remediation in IT Automation, it is crucial to verify if the genera…
cs.CL2024
Execution-Based Evaluation of Natural Language to Bash and PowerShell for Incident Remediation
Ngoc Phuoc An Vo, Brent Paulovicks, Vadim Sheinin
Given recent advancements of Large Language Models (LLMs), code generation tasks attract immense attention for wide application in different domains. In an effort to evaluate and s…
cs.SE2024
CodeSift: An LLM-Based Reference-Less Framework for Automatic Code Validation
Pooja Aggarwal, Oishik Chatterjee, Ting Dai +4
The advent of large language models (LLMs) has greatly facilitated code generation, but ensuring the functional correctness of generated code remains a challenge. Traditional valid…