Google Paper That Caused Global Storage Stocks to Plummet Faces Academic Controversy; Chinese Scholar Accuses It of Being "Seriously False" and "Refusing to Correct Errors": They Used Our Method But Deliberately Avoided Similarities

On March 26, a paper from Google Research claimed that its new algorithm, TurboQuant, can significantly reduce the memory footprint of large AI models. However, Dr. Jianyang Gao, a postdoctoral researcher at ETH Zurich, accused the paper of academic issues, including evading similarities with the RaBitQ algorithm. Gao's team stated that they had communicated with Google multiple times, but Google had not thoroughly corrected the issues. They also plan to present the paper at ICLR 2026. Gao's team believes this has gone beyond academic disagreement and plans to release a technical report to continue seeking a resolution through academic channels.