DeepSWE v1.1

DeepSWE v1.1 is an AI agent model trained to read code, fix bugs, and write new features on its own. Instead of being told the correct answer by humans every step of the way, it was trained by actually running the code and receiving a reward based on whether the problem was solved or not, repeating this process over and over (reinforcement learning) to build up its skills.

Think of it like a student who, after each practice test, is only told the score and then has to figure out on their own how to improve their approach for the next problem. Rather than memorizing an answer key, the model sharpens its practical skills through trial and error. The "v1.1" in the name signals that this is a refined, updated release of an earlier version.

Models like this are often put through benchmarks that measure how well they can handle tasks such as fixing bugs in real software repositories, and their performance is compared against other models.