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We accomplish this using a *deep* language program with several layers of alternating `Attack` and `Refine` modules in the following optimization loop: We accomplish this using a *deep* language program with several layers of alternating `Attack` and `Refine` modules in the following optimization loop:
<figure style="text-align: center;"> <figure style="text-align: center;">
<img src="/images/DSPy-Redteam.png" alt="Overview of DSPy for red-teaming" style="margin: 0 auto; margin-bottom: 20px; display: block;"> <img src="https://www.dropbox.com/scl/fi/4ebg4jrsebbvkpgfs8fjp/feedforward.png?rlkey=tq2saicjukzolhs1fjn30egyf&st=dmuqltlu&dl=0" alt="Overview of DSPy for red-teaming" style="margin: 0 auto; margin-bottom: 20px; display: block;">
<figcaption><i>Figure 1: Overview of DSPy for red-teaming. The DSPy MIPRO optimizer, guided by a LLM as a judge, compiles our language program into an effective red-teamer against Vicuna.</i></figcaption> <figcaption><i>Figure 1: Overview of DSPy for red-teaming. The DSPy MIPRO optimizer, guided by a LLM as a judge, compiles our language program into an effective red-teamer against Vicuna.</i></figcaption>
</figure> </figure>