4 Scientific Research Achievements from Shenzhen Institute of Big Data Research Accepted by ICML 2026
The Shenzhen Institute for Big Data Research has had four of its research papers accepted by ICML 2026, a top-tier international conference in machine learning. Two of the papers introduce novel optimization techniques for large language models: AdaMeZO, an Adam-style zeroth-order optimizer that reduces memory overhead during fine-tuning, and Romberg-ZOGE, a method for higher-order bias reduction in gradient estimation. Another paper presents SCOPE, a framework for efficient video reasoning that uses a cloud-edge collaborative approach to decompose user queries. The fourth paper, MIMOMamba, proposes a new state-space model that jointly models temporal dependencies and cross-channel interactions with linear efficiency. AI
