Chain Dimension Scaling: Communication-Efficient Loop-Style Scaling for Industrial Short-Video Ranking

TL;DR

Industrial recommendation rankers keep scaling in width and depth to billions of parameters, but this increasingly incurs costs in parameter growth, distributed communication overhead, and training inefficiency. We introduce \underline{C}hain \underline{D}imension \underline{S}caling (CDS), a scaling strategy orthogonal to width and depth.