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Large language models (LLMs) have achieved impressive human-like performance across various reasoning tasks.
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Evaluating the evaluation of diversity in natural language generation
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What is inference?
Paul Boghossian. 2014 · 2014
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The comparison between forward and backward chaining
Ajlan Al-Ajlan. 2015 · 2015
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
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Generating diverse translations with sentence codes
Raphael Shu, Hideki Nakayama, and Kyunghyun Cho. 2019 · 2019
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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al. 2020 · 2020
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Did aristotle use a laptop? a question answering benchmark with implicit reasoning strategies
Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, and Jonathan Berant. 2021 · 2021
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Dynamic generation of interpretable inference rules in a neuro-symbolic expert system
Nathaniel Weir and Benjamin Van Durme. 2022 · 2022
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023 · 2023
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Faith and fate: Limits of transformers on compositionality
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jian, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D Hwang, et al. 2023 · 2023
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Critic: Large language models can self-correct with tool-interactive critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, and Weizhu Chen. 2023 · 2023
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Neuro-symbolic forward reasoning
Hikaru Shindo, Devendra Singh Dhami, and Kristian Kersting. 2021 · 2021
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Logic-driven context extension and data augmentation for logical reasoning of text
Siyuan Wang, Wanjun Zhong, Duyu Tang, Zhongyu Wei, Zhihao Fan, Daxin Jiang, Ming Zhou, and Nan Duan. 2021 · 2021
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Identifying and measuring token-level sentiment bias in pre-trained language models with prompts
Apoorv Garg, Deval Srivastava, Zhiyang Xu, and Lifu Huang. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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Neuro-symbolic inductive logic programming with logical neural networks
Prithviraj Sen, Breno WSR de Carvalho, Ryan Riegel, and Alexander Gray. 2022 · 2022
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
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Huihan Li, Yuting Ning, Zeyi Liao, Siyuan Wang, Xiang Lorraine Li, Ximing Lu, Faeze Brahman, Wenting Zhao, Yejin Choi, and Xiang Ren. 2023 · 2023
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Norman Mu, Sarah Chen, Zifan Wang, Sizhe Chen, David Karamardian, Lulwa Aljeraisy, Dan Hendrycks, and David Wagner. 2023 · 2023
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Theo X Olausson, Alex Gu, Benjamin Lipkin, Cedegao E Zhang, Armando Solar-Lezama, Joshua B Tenenbaum, and Roger Levy. 2023 · 2023
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OpenAI. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models
Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim. 2023 · 2023
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Large language models can learn rules
Zhaocheng Zhu, Yuan Xue, Xinyun Chen, Denny Zhou, Jian Tang, Dale Schuurmans, and Hanjun Dai. 2023 · 2023
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Logical structure of fuzzy if-then rules
Vilém Novák and Stephan Lehmke. 2006 · 2029
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