Two-Stage Reinforcement Learning for Sound and Adversarial Test Generation in Code LLMs

Paper recorded by Signals 4 on 2026-09-03 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-03 on arXiv · recorded by Signals 4 on 2026-09-04

Category: cs.CL · 自然语言处理 · first seen 2026-09-04

Abstract

Reinforcement learning (RL) has substantially advanced code generation with large language models (LLMs) through executable feedback. The feedback for coding problems mainly comes from specific test cases, where high-quality test cases are often scarce since they should be both sound and discriminative. We thus turn to study the auto-generation of test cases using the learned model. We find this i

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