阿里巴巴人工智能实验室 7= 590一I) rm 一 下Er (mm) =肪+2mxaM0 [5 (全-2)+o| current plan 1 = int16 * int16 erflow-aware int16 = int8 xint8 ent pl 1=int8 int8 * int8 int32 = int16 1 + int16 x int8 Alibaba Al.Labs 阿里巴巴人工智能实验室 aNCNN 8bit aQNNPACK 8bit aaMNN 8bit TVM Overflow-aware 四ACE Overflow-aware (Assembly) [和| Alibaba AL.Labs 阿里巴巴人工智能实验室 HIFI 4 Alibaba Al.Labs 阿里巴巴人工智能实验室

techniques, like ReAct, where the LLM will keep emitting useless tokens after the response you want. Be aware, generating more tokens requires more computation from the LLM, leading to higher energy consumption receive Prompt Engineering February 2025 61 • Less chance for hallucinations • Make it relationship aware • You get data types • You can sort it Table 4 in the few-shot prompting section shows an example schemas can help establish relationships between different pieces of data and even make the LLM "time-aware" by including date or timestamp fields with specific formats. Here's a simple example: Let's say