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Chain-of-thought (CoT) reasoning has emerged as an effective approach for activating latent capabilities in LLMs.
Adaptive communication receivers
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Boosting the margin: A new explanation for the effectiveness of voting methods
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Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
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Learning to solve arithmetic word problems with verb categorization
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Parsing algebraic word problems into equations
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Virtual adversarial training: a regularization method for supervised and semi-supervised learning
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Commonsenseqa: A question answering challenge targeting commonsense knowledge
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Unsupervised domain adaptation for semantic segmentation via class-balanced self-training
Zou, Y., Yu, Z., Kumar, B., and Wang, J · 2018
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Confidence regularized self-training
Zou, Y., Yu, Z., Liu, X., Kumar, B., and Wang, J · 2019
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Uncertainty-aware self-training for few-shot text classification
Mukherjee, S. and Awadallah, A · 2020
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Training verifiers to solve math word problems
Cobbe, K., Kosaraju, V., Bavarian, M., Chen, M., Jun, H., Kaiser, L., Plappert, M., Tworek, J., Hilton, J., Nakano, R., et al · 2021
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Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies
Geva, M., Khashabi, D., Segal, E., Khot, T., Roth, D., and Berant, J · 2021
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Are nlp models really able to solve simple math word problems?
Patel, A., Bhattamishra, S., and Goyal, N · 2021
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Contrastive chain-of-thought prompting
Chia, Y. K., Chen, G., Tuan, L. A., Poria, S., and Bing, L · 2023
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A survey of reasoning with foundation models
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Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models
Wang, L., Xu, W., Lan, Y., Hu, Z., Lan, Y., Lee, R. K.-W., and Lim, E.-P · 2023
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Self-training: A survey
Amini, M.-R., Feofanov, V., Pauletto, L., Hadjadj, L., Devijver, E., and Maximov, Y · 2024
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Navigate through enigmatic labyrinth a survey of chain of thought reasoning: Advances, frontiers and future
Chu, Z., Chen, J., Chen, Q., Yu, W., He, T., Wang, H., Peng, W., Liu, M., Qin, B., and Liu, T · 2024
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Debiased self-training for semi-supervised learning
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Self-training converts weak learners to strong learners in mixture models
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Large language models are zero-shot reasoners, 2022
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Self-consistency improves chain of thought reasoning in language models
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Chain-of-thought prompting elicits reasoning in large language models
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A survey on deep semi-supervised learning
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Deductive verification of chain-of-thought reasoning
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Re-reading improves reasoning in large language models
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Evaluation of openai o1: Opportunities and challenges of agi
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