Logic Problem Solving And Insight
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%20have%20shown%20amazing%20performance%20on%20tasks%20that%20require%20planning%20and%20reasoning.%20Motivated%20by%20this%2C%20we%20investigate%20the%20internal%20mechanisms%20that%20underpin%20a%20network's%20ability%20to%20perform%20complex%20logical%20reasoning.%20We%20first%20construct%20a%20synthetic%20propositional%20logic%20problem%20that%20serves%20as%20a%20concrete%20test-bed%20for%20network%20training%20and%20evaluation.%20Crucially%2C%20this%20problem%20demands%20nontrivial%20planning%20to%20solve.%20We%20perform%20our%20study%20on%20two%20fronts.%20First%2C%20we%20pursue%20an%20understanding%20of%20precisely%20how%20a%20three-layer%20transformer%2C%20trained%20from%20scratch%20and%20attains%20perfect%20test%20accuracy%2C%20solves%20this%20problem.%20We%20are%20able%20to%20identify%20certain%20planning%20and%20reasoning%20mechanisms%20in%20the%20network%20that%20necessitate%20cooperation%20between%20the%20attention%20blocks%20to%20implement%20the%20desired%20logic.%20Second%2C%20we%20study%20how%20pretrained%20LLMs%2C%20namely%20Mistral-7B%20and%20Gemma-2-9B%2C%20solve%20this%20problem.%20We%20characterize%20their%20reasoning%20circuits%20through%20causal%20intervention%20experiments%2C%20providing%20necessity%20and%20sufficiency%20evidence%20for%20the%20circuits.%20We%20find%20evidence%20suggesting%20that%20the%20two%20models'%20latent%20reasoning%20strategies%20are%20surprisingly%20similar%2C%20and%20human-like.%20Overall%2C%20our%20work%20systemically%20uncovers%20novel%20aspects%20of%20small%20and%20large%20transformers%2C%20and%20continues%20the%20study%20of%20how%20they%20plan%20and%20reason.)































