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LARGE LANGUAGE MODELS ARE ZERO-SHOT REASONERS - NIPS
Web Abstract. Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners … ...
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[2205.11916] LARGE LANGUAGE MODELS ARE ZERO-SHOT …
Web May 24, 2022 Large Language Models are Zero-Shot Reasoners. Pretrained large language models (LLMs) are widely used in many sub-fields of natural language … ...
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Web Zero-shot reasoning is the ability of a large language model to generate responses without any prior specific training. Zero-shot prompting involves posing a question or task to the … ...
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Web Oct 31, 2022 TL;DR: We propose a single zero-shot prompt that elicits effective chain of thought reasoning across diverse benchmarks that require multi-step thinking. Abstract: … ...
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Web May 24, 2022 Figure 1: Example inputs and outputs of GPT-3 with (a) standard Few-shot ([Brown et al., 2020]), (b) Few-shot-CoT ([Wei et al., 2022]), (c) standard Zero-shot, and … ...
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LARGE LANGUAGE MODELS ARE ZERO-SHOT REASONERS - OPENREVIEW
Web Large Language Models are Zero-Shot Reasoners Table 1: Accuracy comparison of Zero-shot-CoT with Zero-shot using Text-davinci-002 (175B). The values on the left side ...
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Web May 24, 2022 Large Language Models are Zero-Shot Reasoners. Pretrained large language models (LLMs) are widely used in many sub-fields of natural language … ...
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Web Jul 8, 2023 For example, Zero-Shot-CoT achieves score gains from 17.7% to 78.7% on MultiArith and from 10.4% to 40.7% on GSM8K. That’s a lot of performance gain! In commonsense reasoning tasks, Zero-Shot ... ...
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Web Large Language Models are Zero-Shot Reasoners Takeshi Kojima The University of Tokyo [email protected] Shixiang Shane Gu Google Research, Brain Team ...
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