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Anecdotally my experience with generative AI is that the valid output space is very tiny especially under a restrictive prompt, i.e. homework question, even sma
by dheatov 2y ago
Anecdotally my experience with generative AI is that the valid output space is very tiny especially under a restrictive prompt, i.e. homework question, even smaller when the output also has to be a correct answer. Using a riskier decoding scheme only generates output that is paraphrastic to each other. So lexical similarity should catch most of the naive prompter.
Subjectively, if a student can knowledge-guide an LLM to generate response from a specific perspective, I think it is very debatable whether such usecase should be outright punished.
- killingtime74 2y agoIndeed, they would just be preparing for industry in that case (guiding the LLM)
- huygens6363 2y agoOk, given that restrictions I can see how you can arrive at a pragmatic solution, so long as we don’t have the illusion this is actually a solution. For example, giving it a small corpus of my previous handwritten work and asking it to respond in the same style is exceedingly easy and very, very hard to detect. Especially if you run a small algo on it afterwards to introduce your category of typos etc. It is only a matter of time before services will pop up for students that automate/wrap this.