Online recommendation is moving into a new phase as transformers begin to reshape how graph-based systems understand users, items, and their hidden connections. The study shows that transformer models ...

Large language models like ChatGPT and Llama-2 are notorious for their extensive memory and computational demands, making them costly to run. Trimming even a small fraction of their size can lead to ...

The transformer-based semantic segmentation approaches, which divide the image into different regions by sliding windows and model the relation inside each window, have achieved outstanding success.

As vision-centric large language models move on-device, performance measured in raw TOPS is no longer enough. Architectures need to be built around real workloads, memory behavior, and sustained ...