AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 4 of 16 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Reinforcement learning (RL) for code agents often uses executable tests to provide binary rewards. With these rewards, Group Relative Policy Optimization (GRPO) assigns identical advantages to test-passing trajectories within each rollout group, overlooking differences in implementation quality and adherence to task re...
This work proposes BiVCoder, a diagnosis-driven multi-agent framework featuring a novel bidirectional code-test diagnosis mechanism, and introduces BiVCoder-SFT, a role-specific instruction fine-tuning scheme.
Large Language Models (LLMs) have demonstrated remarkable potential in automated code generation. However, existing test-driven code generation and refinement frameworks are often hindered by the tests' quality: they typically treat self-generated tests as ground truth, leading to ineffective debugging loops where code...
DBcover is proposed, an LLM-driven database test generation framework that performs white-box, code-aware SQL test generation through contextual reasoning, and substantially outperforms existing fuzzers.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.