One-shot as in ‘given one example’ is the ML term. One-shot as in ‘in a single prompt’ is the colloquial meaning. Both are useful, but it can be confusing when discussing LLMs in ML topics.
The article says that having decompiled some functions helps with decompiling others, so it seems like more than one example could be provided in the context. I think the OP was referring to the fact that only a single prompt created by a human was used. But then it goes off into what appears to be an agentic loop with no hard stopping conditions outside of what the agent decides.
We're essentially trying to map 'traditional' ML terminology to LLMs, it's natural that it'll take some time to get settled. I just thought that one-shot isn't an ideal name for something that might go off into an arbitrarily long loop.
1. Getting an LLM to do something based on a single example
2. Getting an LLM to achieve a goal from a single prompt with no follow-ups
I think both are equally valid.