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Yeah, that was the point of the toddler example. It's very obvious the toddler covered in chocolate likely stole the fudge. My question is how does this train
by gotoeleven 2y ago
Yeah, that was the point of the toddler example. It's very obvious the toddler covered in chocolate likely stole the fudge. My question is how does this training to remove bias not also make it worse at identifying toddler fudge thieves? This bias training afaict is literally training the LLM to not understand what likely means. In the example from the article, "C" is in my opinion not a good answer--it certainly isn't objectively correct like people are trying to assert.
If I'd like my LLM to not rely on circumstantial or statistical evidence and only use hard forensic evidence to answer me, then that seems like something I should be able to ask for but making it the default mode of operation will make the answers strictly less correct.
- grayhatter 2y agodoes it? I wouldn't expect an LLM that was trained with care to answer based on context, and to exclude bias to still be able to answer correctly when provided with context. Did I miss something and there's a reason to suspect that fine tuning to remove bias would also prevent it from predicting based on provided context? Or did you just make up that example because it might be interesting if it was true?