Fetching the paper…
Reading the bibliography…
Our work demonstrates that large language model (LLM) pre-trained on texts can not only solve pure math word problems, but also physics word problems, whose solution requires calculation and inference based on prior physical knowledge.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
Earlier work this paper cites.
Lu Lu, Pengzhan Jin, and George Em Karniadakis. 2019 · 1910
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2009
Earlier work this paper cites.
Parsing algebraic word problems into equations
Rik Koncel-Kedziorski, Hannaneh Hajishirzi, Ashish Sabharwal, Oren Etzioni, and Siena Dumas Ang. 2015 · 2015
Earlier work this paper cites.
Solving general arithmetic word problems
Subhro Roy and Dan Roth. 2015 · 2015
Earlier work this paper cites.
Hybrid of qualitative and quantitative knowledge models for solving physics word problems
Savitha Sam Abraham and Deepak Khemani. 2016 · 2016
Earlier work this paper cites.
How well do computers solve math word problems? large-scale dataset construction and evaluation
Danqing Huang, Shuming Shi, Chin-Yew Lin, Jian Yin, and Wei-Ying Ma. 2016 · 2016
Earlier work this paper cites.
Machine solver for physics word problems
Megan Leszczynski and Jose Moreira. 2016 · 2016
Earlier work this paper cites.
Deep neural solver for math word problems
Yan Wang, Xiaojiang Liu, and Shuming Shi. 2017 · 2017
Cited alongside, same era.
An overview of problem solving studies in physics education
Elif Ince. 2018 · 2018
Cited alongside, same era.
Translating a math word problem to a expression tree
Lei Wang, Yan Wang, Deng Cai, Dongxiang Zhang, and Xiaojiang Liu. 2018a · 2018
Cited alongside, same era.
Mathqa: Towards interpretable math word problem solving with operation-based formalisms
Aida Amini, Saadia Gabriel, Shanchuan Lin, Rik Koncel-Kedziorski, Yejin Choi, and Hannaneh Hajishirzi. 2019 · 2019
Cited alongside, same era.
Neural sequence modeling in physical language understanding
Avi Bleiweiss. 2019 · 2019
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova. 2019 · 2019
The gap of semantic parsing: A survey on automatic math word problem solvers
Dongxiang Zhang, Lei Wang, Luming Zhang, Bing Tian Dai, and Heng Tao Shen. 2019 · 2019
Later among the works it cites.
Geoqa: A geometric question answering benchmark towards multimodal numerical reasoning
Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric Xing, and Liang Lin. 2021 · 2021
Later among the works it cites.
Are nlp models really able to solve simple math word problems?
Arkil Patel, Satwik Bhattamishra, and Navin Goyal. 2021 · 2021
Later among the works it cites.
A neural network solves, explains, and generates university math problems by program synthesis and few-shot learning at human level
Iddo Drori, Sarah Zhang, Reece Shuttleworth, Leonard Tang, Albert Lu, Elizabeth Ke, Kevin Liu, Linda Chen, Sunny Tran, Newman Cheng, et al. 2022 · 2022
Later among the works it cites.
Logicsolver: Towards interpretable math word problem solving with logical prompt-enhanced learning
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
A goal-driven tree-structured neural model for math word problems
Z. Xie and S. Sun. 2019 · 2019
Cited alongside, same era.
Mathdqn: Solving arithmetic word problems via deep reinforcement learning
Lei Wang, Dongxiang Zhang, Lianli Gao, Jingkuan Song, Long Guo, and Heng Tao Shen. 2018b
Cited in the paper.
Zhicheng Yang, Jinghui Qin, Jiaqi Chen, Liang Lin, and Xiaodan Liang. 2022 · 2022
Later among the works it cites.
Mathprompter: Mathematical reasoning using large language models
Shima Imani, Liang Du, and Harsh Shrivastava. 2023 · 2023
Closest in time.
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al. 2023 · 2023
Closest in time.