A large body of research since the 1980s empirically observed that large neural networks can be compressed orsparsified toasmallfraction oftheiroriginal sizewhilemaintaining theirpredictive accuracy[14-16,20,23,29,45].

However,existingmodelsand benchmarks are commonly tailored to specific tasks, falling short of capturing the full complexity of online shopping. Large Language Models (LLMs), with their multi-task and few-shot learning abilities, have the potential to profoundly transform online shopping byalleviating task-specific engineering effortsandby providing users with interactiveconversations.