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Logical reasoning is a fundamental aspect of human intelligence and a key component of tasks like problem-solving and decision-making.
What you always wanted to know about datalog(and never dared to ask)
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Programming in PROLOG
William F Clocksin and Christopher S Mellish. 2003 · 2003
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Applying expert system technology to code reuse with pyke
Bruce Frederiksen. 2008 · 2008
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Artificial Intelligence: foundations of computational agents
David L Poole and Alan K Mackworth. 2010 · 2010
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Transformers as soft reasoners over language
Peter Clark, Oyvind Tafjord, and Kyle Richardson. 2020 · 2020
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Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He. 2020 · 2020
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ProofWriter: Generating implications, proofs, and abductive statements over natural language
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Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W Cohen. 2022 · 2022
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Training compute-optimal large language models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, et al. 2022 · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Fifty years of prolog and beyond
Philipp Körner, Michael Leuschel, João Barbosa, Vítor Santos Costa, Verónica Dahl, Manuel V Hermenegildo, Jose F Morales, Jan Wielemaker, Daniel Diaz, Salvador Abreu, et al. 2022 · 2022
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Internet-augmented language models through few-shot prompting for open-domain question answering
Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, and Nikolai Grigorev. 2022 · 2022
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Chatgpt: Optimizing language models for dialogue
OpenAI. 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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Neupsl: Neural probabilistic soft logic
Connor Pryor, Charles Dickens, Eriq Augustine, Alon Albalak, William Wang, and Lise Getoor. 2022 · 2022
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Weakly supervised neural symbolic learning for cognitive tasks
Jidong Tian, Yitian Li, Wenqing Chen, Liqiang Xiao, Hao He, and Yaohui Jin. 2022 · 2022
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Large language models still can’t plan (a benchmark for llms on planning and reasoning about change)
Karthik Valmeekam, Alberto Olmo, Sarath Sreedharan, and Subbarao Kambhampati. 2022 · 2022
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Deductive verification of chain-of-thought reasoning
Zhan Ling, Yunhao Fang, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, and Hao Su. 2023 · 2023
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Faithful chain-of-thought reasoning
Qing Lyu, Shreya Havaldar, Adam Stein, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, and Chris Callison-Burch. 2023 · 2023
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OpenAI. 2023 · 2023
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Logic-lm: Empowering large language models with symbolic solvers for faithful logical reasoning
Liangming Pan, Alon Albalak, Xinyi Wang, and William Yang Wang. 2023 · 2023
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Generating natural language proofs with verifier-guided search
Kaiyu Yang, Jia Deng, and Danqi Chen. 2022 · 2022
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Least-to-most prompting enables complex reasoning in large language models
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Chatcot: Tool-augmented chain-of-thought reasoning on chat-based large language models
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
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Google bard
Google. 2023 · 2023
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Towards reasoning in large language models: A survey
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Code llama: Open foundation models for code
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Language models are greedy reasoners: A systematic formal analysis of chain-of-thought
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