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glaugh | 1 year ago

Thank you (and teMPOral) for these comments, this sounds potentially useful to me.

I hate to ask this, but I'm struggling to find any thorough posts or articles or papers about this, do you have any links you could point me toward?

discuss

order

jacobr1|1 year ago

Here is a short example that came up for me last week.

I had a set of documents I wanted to classify according a taxonomy that is well known (so it is exists in the training data of all the major llm models I tested)

If I have prompt like, `You are an expert classification system. Using the Classification Approach Foo, consider the following and output the category in JSON format, such as {"class":"bar"} `

This works ok, but it works much better if I tell it to output {"class":"bar", "reason": "baz"} and improved with some other approaches like adding "related_class" or "parent_category" which would otherwise be redundant.

Also including some few-shot examples helped, but the biggest benefit came from the "reason" field. Trying justification or other synonyms seems to produce the same output.

I suspect this is something similar to CoT.

potatoman22|1 year ago

Have you tested moving the "reason" field before the "class" field? That may encourage better CoT instead of having the model justify the class after it already picked it. Anecdotally, I saw a 5% boost in performance from a NER system from having the model output the entity's class at the end rather than the beginning.

te_chris|1 year ago

This has worked for me for sentiment classification, i had a score and a summary field and the results were much more accurate.

andai|1 year ago

Does it still work if the class field is output before the reason?

glaugh|1 year ago

Great, thank you (and hedgehog), that makes sense

hedgehog|1 year ago

Speaking only for myself these ideas are a combination of things I've seen scanning new papers and informal discussions with other people working in the area. Feel free to shoot me an e-mail though, maybe I can point you somewhere more specific.

Edit: The "verbosity sink" name is inspired by the idea from the paper below although they're not actually at all the same thing.

https://arxiv.org/abs/2309.17453