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Language Models can Solve Computer Tasks

NeurIPS 2023 · Large language models › Reasoning and chain of thought · approach: Theory of autoregressive reasoning · 67 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add RCI to zero-shot promptinggpt-3.5-turbo · GSM8Kaccuracy: 77.95 -> 85.43Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · MultiArithaccuracy: 94.48 -> 97.64Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · AddSubaccuracy: 88.58 -> 89.76Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · SVAMPaccuracy: 80.70 -> 84.65Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · SingleEqaccuracy: 86.61 -> 94.49Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · AQuAaccuracy: 60.23 -> 67.32Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · CommonSenseQAaccuracy: 64.56 -> 68.11Helped
Add RCI to zero-shot promptinggpt-3.5-turbo · StrategyQAaccuracy: 48.81 -> 61.81Helped
Add RCI to Zero-Shot CoTgpt-3.5-turbo · GSM8Kaccuracy: 82.28 -> 86.22Helped
Add RCI to Few-Shot CoTgpt-3.5-turbo · MultiArithaccuracy: 98.82 -> 99.21Helped
Add RCI to Few-Shot CoTgpt-3.5-turbo · AddSubaccuracy: 89.37 -> 90.55Helped
Add RCI to Few-Shot CoTgpt-3.5-turbo · SVAMPaccuracy: 83.46 -> 87.40Helped

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