Chain-of-thought prompting, by including intermediate reasoning steps in few-shot examples, elicits strong reasoning abilities in large language models on arithmetic, commonsense, and symbolic tasks.
Solving General Arithmetic Word Problems
3 Pith papers cite this work. Polarity classification is still indexing.
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Latent-GRPO stabilizes reinforcement learning in latent space, delivering 7.86 Pass@1 gains on low-difficulty tasks over latent baselines and 4.27 points over explicit GRPO on high-difficulty tasks with 3-4x shorter reasoning chains.
PaLM 2 reports state-of-the-art results on language, reasoning, and multilingual tasks with improved efficiency over PaLM.
citing papers explorer
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-thought prompting, by including intermediate reasoning steps in few-shot examples, elicits strong reasoning abilities in large language models on arithmetic, commonsense, and symbolic tasks.
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Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning
Latent-GRPO stabilizes reinforcement learning in latent space, delivering 7.86 Pass@1 gains on low-difficulty tasks over latent baselines and 4.27 points over explicit GRPO on high-difficulty tasks with 3-4x shorter reasoning chains.
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PaLM 2 Technical Report
PaLM 2 reports state-of-the-art results on language, reasoning, and multilingual tasks with improved efficiency over PaLM.