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Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans.
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
Aida Amini, Saadia Gabriel, Peter Lin, Rik Koncel-Kedziorski, Yejin Choi, and Hannaneh Hajishirzi. 2019 · 1905
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ARQMath Lab: An Incubator for Semantic Formula Search in zbMATH Open?
Philipp Scharpf, Moritz Schubotz, Andre Greiner-Petter, Malte Ostendorff, Olaf Teschke, and Bela Gipp. 2020 · 2012
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Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems
Wang Ling, Dani Yogatama, Chris Dyer, and Phil Blunsom. 2017 · 2017
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Transforming Scanned zbMATH Volumes to LaTeX: Planning the Next Level Digitisation
Marco Beck, Isabel Beckenbach, Thomas Hartmann, Moritz Schubotz, and Olaf Teschke. 2020 · 2020
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Training Verifiers to Solve Math Word Problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
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Measuring Mathematical Problem Solving With the MATH Dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021
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Language Model is all You Need: Natural Language Understanding as Question Answering. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . 7803–7807
Mahdi Namazifar, Alexandros Papangelis, Gokhan Tur, and Dilek Hakkani-Tür. 2021 · 2021
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Advancing Math-Aware Search: The ARQMath-3 Lab at CLEF 2022. In Advances in Information Retrieval , Matthias Hagen, Suzan Verberne, Craig Macdonald, Christin Seifert, Krisztian Balog, Kjetil Nørvåg, and Vinay Setty (Eds.). Springer International Publishing, Cham, 408–415
Behrooz Mansouri, Anurag Agarwal, Douglas W. Oard, and Richard Zanibbi. 2022 · 2022
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Llemma: An Open Language Model For Mathematics
Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, and Sean Welleck. 2023 · 2023
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Aniruddha Deb, Neeva Oza, Sarthak Singla, Dinesh Khandelwal, Dinesh Garg, and Parag Singla. 2023 · 2023
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ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Zhibin Gou, Zhihong Shao, Yeyun Gong, yelong shen, Yujiu Yang, Minlie Huang, Nan Duan, and Weizhu Chen. 2023 · 2023
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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, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
Cited alongside, same era.
Evaluating Open-Domain Question Answering in the Era of Large Language Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, Toronto, Canada, 5591–5606
Ehsan Kamalloo, Nouha Dziri, Charles Clarke, and Davood Rafiei. 2023 · 2023
Cited alongside, same era.
Large Language Models: Their Success and Impact
Spyros Makridakis, Fotios Petropoulos, and Yanfei Kang. 2023 · 2023
Cited alongside, same era.
ChatGPT and large language models in academia: opportunities and challenges
Jesse G Meyer, Ryan J Urbanowicz, Patrick C N Martin, Karen O’Connor, Ruowang Li, Pei-Chen Peng, Tiffani J Bright, Nicholas Tatonetti, Kyoung Jae Won, Graciela Gonzalez-Hernandez, and Jason H Moore. 2023 · 2023
One Blade for One Purpose: Advancing Math Information Retrieval Using Hybrid Search. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (<conf-loc>, <city>Taipei</city>, <country>Taiwan</country>, </conf-loc>) (SIGIR ’23) . Association for Computing Machinery, New York, NY, USA, 141–151
Wei Zhong, Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2023 · 2023
Later among the works it cites.
Aojun Zhou, Ke Wang, Zimu Lu, Weikang Shi, Sichun Luo, Zipeng Qin, Shaoqing Lu, Anya Jia, Linqi Song, Mingjie Zhan, and Hongsheng Li. 2023 · 2023
Later among the works it cites.
Pengfei Hong, Deepanway Ghosal, Navonil Majumder, Somak Aditya, Rada Mihalcea, and Soujanya Poria. 2024 · 2024
Closest in time.
Understanding LLMs: A Comprehensive Overview from Training to Inference
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Cited alongside, same era.
Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, and Dan Roth. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
TEIMMA: The First Content Reuse Annotator for Text, Images, and Math. In 2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL) . 271–273
Ankit Satpute, Andre Greiner-Petter, Moritz Schubotz, Norman Meuschke, Akiko Aizawa, Olaf Teschke, and Bela Gipp. 2023 · 2023
Cited alongside, same era.
Llama 2: Open Foundation and Fine-Tuned Chat Models
LLaMa-2 Team. 2023 · 2023
Cited alongside, same era.
Who’s the Best Detective? LLMs vs. MLs in Detecting Incoherent Fourth Grade Math Answers
Felipe Urrutia and Roberto Araya. 2023 · 2023
Cited alongside, same era.
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, and Wenhu Chen. 2023 · 2023
Cited alongside, same era.
Effective Math-Aware Ad-Hoc Retrieval based on Structure Search and Semantic Similarities
Wei Zhong. 2023 · 2023
Cited alongside, same era.
Can Generative LLMs Create Query Variants for Test Collections? An Exploratory Study. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (Taipei,Taiwan) (SIGIR ’23) . Association for Computing Machinery, New York, NY, USA, 1869–1873
Marwah Alaofi, Luke Gallagher, Mark Sanderson, Falk Scholer, and Paul Thomas. 2023a
Cited in the paper.
Yiheng Liu, Hao He, Tianle Han, Xu Zhang, Mengyuan Liu, Jiaming Tian, Yutong Zhang, Jiaqi Wang, Xiaohui Gao, Tianyang Zhong, Yi Pan, Shaochen Xu, Zihao Wu, Zhengliang Liu, Xin Zhang, Shu Zhang, Xintao Hu, Tuo Zhang, Ning Qiang, Tianming Liu, and Bao Ge. 2024 · 2024
Closest in time.
Yujun Mao, Yoon Kim, and Yilun Zhou. 2024 · 2024
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Mathematical discoveries from program search with large language models
Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, and Push. 2024 · 2024
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Code Llama: Open Foundation Models for Code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, and Gabriel Synnaeve. 2024 · 2024
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Taxonomy of Mathematical Plagiarism. In 46th European Conference on Information Retrieval (ECIR) . Springer, Glasgow, Scotland
Ankit Satpute, Andre Greiner-Petter, Noah Giessing, Isabel Beckenbach, Moritz Schubotz, Olaf Teschke, Akiko Aizawa, and Bela Gipp. 2024 · 2024
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Solving olympiad geometry without human demonstrations
Trieu H Trinh, Yuhuai Wu, Quoc V Le, He He, and Thang Luong. 2024 · 2024
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Who’s the Best Detective? Large Language Models vs. Traditional Machine Learning in Detecting Incoherent Fourth Grade Math Answers
Felipe Urrutia and Roberto Araya. 2024 · 2024
Closest in time.