1 citations · 2 across the 13 of their papers we have counts for
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Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents
Jingjie Ning, Shanshan Zhong, Xiaochuan Li +1
AI research agents combine public information and experimental feedback to produce measurable results. The Discovery Certification Protocol (DCP) turns an outcome claim into an exe…
The Implementation Lottery: Auditing Idea Reliability in Automated Research
Jingjie Ning, Shanshan Zhong, Xiaochuan Li +2
Automated research agents use program scores to judge ideas. We call variation in this evidence across implementations the implementation lottery. We introduce an Idea Reliability…
Auto Research for Materials: Auditable AI-Scientist Workflows with Held-Out Transfer
Jingjie Ning, Xiaochuan Li, Shanshan Zhong +2
Auto Research uses language-model agents to propose, implement, and evaluate machine-learning changes in a closed loop, but is usually judged by its terminal pipeline. A terminal s…
Auto Research with Specialist Agents Develops Effective and Non-Trivial Training Recipes
Jingjie Ning, Xiaochuan Li, Ji Zeng +2
We study auto research as a closed empirical loop driven by external measurement. Each submitted trial carries a hypothesis, an executable code edit, an evaluator-owned outcome, an…