background pattern

Jigsaw

Large Language Models meet Program Synthesis

微软研究院博客

A flowchart showing inputs pre-processed before being fed into large language models including GPT-3, Codex, and others. The post-process output is returned to the end-user for verification. If they find the output incorrect, it is edited by them, and the learning is fed back into the pre-process and post-process mechanisms to improve them further.
微软研究院博客

| Rahul Sharma, Suresh Parthasarathy, Sriram Rajamani, Nagarajan Natarajan, 和 Arun Iyer

Large pre-trained language models such as GPT-3, Codex, and others can be tuned to generate code from natural language specifications of programmer intent. Such automated models have the potential to improve productivity for every programmer in the world. But since…