AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 4 of 11 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.
This work studies uncertainty-aware rollback decoding, an inference-time strategy that uses uncertainty signals to identify unreliable generation regions and roll back to earlier valid prefixes without retraining the model.
GRAF, a black box fuzzing framework for GDBMS query engines, introduces graph context aware query generation based on cascading dependency resolution and applies five graph specific mutation operators guided by execution state feedback.
The core of VaryBalance is that, compared to LLM-generated texts, there is a greater difference between human texts and their rewritten version via LLMs, and quantifies this through Mean Squared Deviation and distinguishes human texts and LLM-generated texts.
This work proposes Explore-Construct-Verify (ECV), a three-stage framework for API KG construction using large language models (LLMs), which preserves LLMs’ ability to discover domain-specific knowledge while enabling efficient post-hoc validation.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.