NovelSeek: When Agent Becomes the Scientist -- Building Closed-Loop System from Hypothesis to Verification

Artificial Intelligence (AI) is accelerating the transformation of scientificresearch paradigms, not only enhancing research efficiency but also drivinginnovation. We introduce NovelSeek, a unified closed-loop multi-agent frameworkto conduct Autonomous Scientific Research (ASR) across various scientificresearch fields, enabling researchers to tackle complicated problems in thesefields with unprecedented speed and precision. NovelSeek highlights three keyadvantages: 1) Scalability: NovelSeek has demonstrated its versatility across12 scientific research tasks, capable of generating innovative ideas to enhancethe performance of baseline code. 2) Interactivity: NovelSeek provides aninterface for human expert feedback and multi-agent interaction in automatedend-to-end processes, allowing for the seamless integration of domain expertknowledge. 3) Efficiency: NovelSeek has achieved promising performance gains inseveral scientific fields with significantly less time cost compared to humanefforts. For instance, in reaction yield prediction, it increased from 27.6% to35.4% in just 12 hours; in enhancer activity prediction, accuracy rose from0.52 to 0.79 with only 4 hours of processing; and in 2D semantic segmentation,precision advanced from 78.8% to 81.0% in a mere 30 hours.