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Mathematical reasoning poses a significant challenge for language models due to its complex and structured nature.
The isabelle framework
M. Wenzel, L. C. Paulson, and T. Nipkow · 2008
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Generative language modeling for automated theorem proving
S. Polu and I. Sutskever · 2009
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Three years of experience with sledgehammer, a practical link between automatic and interactive theorem provers
L. C. Paulson · 2010
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High-dimensional continuous control using generalized advantage estimation
J. Schulman, P. Moritz, S. Levine, M. Jordan, and P. Abbeel · 2015
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Fasttext. zip: Compressing text classification models
A. Joulin, E. Grave, P. Bojanowski, M. Douze, H. Jégou, and T. Mikolov · 2016
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Decoupled weight decay regularization
I. Loshchilov and F. Hutter · 2017
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Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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Measuring massive multitask language understanding
D. Hendrycks, C. Burns, S. Basart, A. Zou, M. Mazeika, D. Song, and J. Steinhardt · 2020
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Approximating kl divergence, 2020
J. Schulman · 2020
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Program synthesis with large language models
J. Austin, A. Odena, M. Nye, M. Bosma, H. Michalewski, D. Dohan, E. Jiang, C. Cai, M. Terry, Q. Le, et al · 2021
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Evaluating large language models trained on code
M. Chen, J. Tworek, H. Jun, Q. Yuan, H. P. de Oliveira Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, A. Ray, R. Puri, G. Krueger, M. Petrov, H. Khlaaf, G. Sastry, P. Mishkin, B. Chan, S. Gray, N. Ryder, M. Pavlov, A. Power, L. Kaiser, M. Bavarian, C. Winter, P. Tillet, F. P. Such, D. Cummings, M. Plappert, F. Chantzis, E. Barnes, A. Herbert-Voss, W. H. Guss, A. Nichol, A. Paino, N. Tezak, J. Tang, I. Babuschkin, S. Balaji, S. Jain, W. Saunders, C. Hesse, A. N. Carr, J. Leike, J. Achiam, V. Misra, E. Morikawa, A. Radford, M. Knight, M. Brundage, M. Murati, K. Mayer, P. Welinder, B. McGrew, D. Amodei, S. McCandlish, I. Sutskever, and W. Zaremba · 2021
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Training verifiers to solve math word problems
K. Cobbe, V. Kosaraju, M. Bavarian, M. Chen, H. Jun, L. Kaiser, M. Plappert, J. Tworek, J. Hilton, R. Nakano, et al · 2021
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Measuring mathematical problem solving with the math dataset
D. Hendrycks, C. Burns, S. Kadavath, A. Arora, S. Basart, E. Tang, D. Song, and J. Steinhardt · 2021
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Minif2f: a cross-system benchmark for formal olympiad-level mathematics
K. Zheng, J. M. Han, and S. Polu · 2021
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W. Chen, X. Ma, X. Wang, and W. W. Cohen · 2022
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Glm: General language model pretraining with autoregressive blank infilling
Z. Du, Y. Qian, X. Liu, M. Ding, J. Qiu, Z. Yang, and J. Tang · 2022
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Draft, sketch, and prove: Guiding formal theorem provers with informal proofs
A. Q. Jiang, S. Welleck, J. P. Zhou, W. Li, J. Liu, M. Jamnik, T. Lacroix, Y. Wu, and G. Lample · 2022
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Solving quantitative reasoning problems with language models
A. Lewkowycz, A. Andreassen, D. Dohan, E. Dyer, H. Michalewski, V. V. Ramasesh, A. Slone, C. Anil, I. Schlag, T. Gutman-Solo, Y. Wu, B. Neyshabur, G. Gur-Ari, and V. Misra · 2022
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LILA: A unified benchmark for mathematical reasoning
S. Mishra, M. Finlayson, P. Lu, L. Tang, S. Welleck, C. Baral, T. Rajpurohit, O. Tafjord, A. Sabharwal, P. Clark, and A. Kalyan · 2022
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Training language models to follow instructions with human feedback
L. Ouyang, J. Wu, X. Jiang, D. Almeida, C. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, et al · 2022
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Challenging big-bench tasks and whether chain-of-thought can solve them
M. Suzgun, N. Scales, N. Schärli, S. Gehrmann, Y. Tay, H. W. Chung, A. Chowdhery, Q. V. Le, E. H. Chi, D. Zhou, et al · 2022
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Chain-of-thought prompting elicits reasoning in large language models
J. Wei, X. Wang, D. Schuurmans, M. Bosma, B. Ichter, F. Xia, E. H. Chi, Q. V. Le, and D. Zhou · 2022
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Gemini: A family of highly capable multimodal models
R. Anil, S. Borgeaud, Y. Wu, J. Alayrac, J. Yu, R. Soricut, J. Schalkwyk, A. M. Dai, A. Hauth, K. Millican, D. Silver, S. Petrov, M. Johnson, I. Antonoglou, J. Schrittwieser, A. Glaese, J. Chen, E. Pitler, T. P. Lillicrap, A. Lazaridou, O. Firat, J. Molloy, M. Isard, P. R. Barham, T. Hennigan, B. Lee, F. Viola, M. Reynolds, Y. Xu, R. Doherty, E. Collins, C. Meyer, E. Rutherford, E. Moreira, K. Ayoub, M. Goel, G. Tucker, E. Piqueras, M. Krikun, I. Barr, N. Savinov, I. Danihelka, B. Roelofs, A. White, A. Andreassen, T. von Glehn, L. Yagati, M. Kazemi, L. Gonzalez, M. Khalman, J. Sygnowski, and et al · 2023
Seallms - large language models for southeast asia
X. Nguyen, W. Zhang, X. Li, M. M. Aljunied, Q. Tan, L. Cheng, G. Chen, Y. Deng, S. Yang, C. Liu, H. Zhang, and L. Bing · 2023
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OpenAI · 2023
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Openwebmath: An open dataset of high-quality mathematical web text
K. Paster, M. D. Santos, Z. Azerbayev, and J. Ba · 2023
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Direct preference optimization: Your language model is secretly a reward model
R. Rafailov, A. Sharma, E. Mitchell, S. Ermon, C. D. Manning, and C. Finn · 2023
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Language models are multilingual chain-of-thought reasoners
F. Shi, M. Suzgun, M. Freitag, X. Wang, S. Srivats, S. Vosoughi, H. W. Chung, Y. Tay, S. Ruder, D. Zhou, D. Das, and J. Wei · 2023
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Llemma: An open language model for mathematics
Z. Azerbayev, H. Schoelkopf, K. Paster, M. D. Santos, S. McAleer, A. Q. Jiang, J. Deng, S. Biderman, and S. Welleck · 2023
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J. Bai, S. Bai, Y. Chu, Z. Cui, K. Dang, X. Deng, Y. Fan, W. Ge, Y. Han, F. Huang, et al · 2023
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Weak-to-strong generalization: Eliciting strong capabilities with weak supervision
C. Burns, P. Izmailov, J. H. Kirchner, B. Baker, L. Gao, L. Aschenbrenner, Y. Chen, A. Ecoffet, M. Joglekar, J. Leike, et al · 2023
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Chatglm3 series: Open bilingual chat llms, 2023
ChatGLM3 Team · 2023
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Redpajama: an open dataset for training large language models, Oct. 2023
T. Computer · 2023
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PAL: program-aided language models
L. Gao, A. Madaan, S. Zhou, U. Alon, P. Liu, Y. Yang, J. Callan, and G. Neubig · 2023
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Tora: A tool-integrated reasoning agent for mathematical problem solving
Z. Gou, Z. Shao, Y. Gong, Y. Shen, Y. Yang, M. Huang, N. Duan, and W. Chen · 2023
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Hai-llm: 高效且轻量的大模型训练工具, 2023
High-flyer · 2023
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Preference ranking optimization for human alignment
F. Song, B. Yu, M. Li, H. Yu, F. Huang, Y. Li, and H. Wang · 2023
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Embracing change and resetting expectations, 2023
T. Tao · 2023
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Llama 2: Open foundation and fine-tuned chat models
H. Touvron, L. Martin, K. Stone, P. Albert, A. Almahairi, Y. Babaei, N. Bashlykov, S. Batra, P. Bhargava, S. Bhosale, D. Bikel, L. Blecher, C. Canton-Ferrer, M. Chen, G. Cucurull, D. Esiobu, J. Fernandes, J. Fu, W. Fu, B. Fuller, C. Gao, V. Goswami, N. Goyal, A. Hartshorn, S. Hosseini, R. Hou, H. Inan, M. Kardas, V. Kerkez, M. Khabsa, I. Kloumann, A. Korenev, P. S. Koura, M. Lachaux, T. Lavril, J. Lee, D. Liskovich, Y. Lu, Y. Mao, X. Martinet, T. Mihaylov, P. Mishra, I. Molybog, Y. Nie, A. Poulton, J. Reizenstein, R. Rungta, K. Saladi, A. Schelten, R. Silva, E. M. Smith, R. Subramanian, X. E. Tan, B. Tang, R. Taylor, A. Williams, J. X. Kuan, P. Xu, Z. Yan, I. Zarov, Y. Zhang, A. Fan, M. Kambadur, S. Narang, A. Rodriguez, R. Stojnic, S. Edunov, and T. Scialom · 2023
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Cmath: Can your language model pass chinese elementary school math test?, 2023
T. Wei, J. Luan, W. Liu, S. Dong, and B. Wang · 2023
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Speculative decoding: Exploiting speculative execution for accelerating seq2seq generation
H. Xia, T. Ge, P. Wang, S.-Q. Chen, F. Wei, and Z. Sui · 2023
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Tree of thoughts: Deliberate problem solving with large language models
S. Yao, D. Yu, J. Zhao, I. Shafran, T. L. Griffiths, Y. Cao, and K. Narasimhan · 2023
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Metamath: Bootstrap your own mathematical questions for large language models
L. Yu, W. Jiang, H. Shi, J. Yu, Z. Liu, Y. Zhang, J. T. Kwok, Z. Li, A. Weller, and W. Liu · 2023
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Mammoth: Building math generalist models through hybrid instruction tuning
X. Yue, X. Qu, G. Zhang, Y. Fu, W. Huang, H. Sun, Y. Su, and W. Chen · 2023
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AGIEval: A human-centric benchmark for evaluating foundation models
W. Zhong, R. Cui, Y. Guo, Y. Liang, S. Lu, Y. Wang, A. Saied, W. Chen, and N. Duan · 2023
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Deepseek LLM: scaling open-source language models with longtermism
DeepSeek-AI · 2024
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Deepseek-coder: When the large language model meets programming – the rise of code intelligence, 2024
D. Guo, Q. Zhu, D. Yang, Z. Xie, K. Dong, W. Zhang, G. Chen, X. Bi, Y. Wu, Y. K. Li, F. Luo, Y. Xiong, and W. Liang · 2024
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Solving olympiad geometry without human demonstrations
T. H. Trinh, Y. Wu, Q. V. Le, H. He, and T. Luong · 2024
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H. Xia, Z. Yang, Q. Dong, P. Wang, Y. Li, T. Ge, T. Liu, W. Li, and Z. Sui · 2024
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