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Geometry problem solving presents a formidable challenge within the NLP community.
J. Cho, J. Lei, H. Tan, M. Bansal, Unifying vision-and-language tasks via text generation, in: M. Meila, T. Zhang (Eds.), Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, Vol. 139 of Proceedings of Machine Learning Research, PMLR, 2021, pp. 1931–1942
1942
Earlier work this paper cites.
doi:10.1145/1460361.1460381
H. L. Gelernter, J. R. Hansen, D. W. Loveland, Empirical explorations of the geometry theorem machine, in: R. M. Bennett (Ed.), Papers presented at the 1960 western joint IRE-AIEE-ACM computer conference, IRE-AIEE-ACM 1960 (Western), San Francisco, California, USA, May 3-5, 1960, ACM, 1960, pp. 143–149 · 1960
Earlier work this paper cites.
doi:10.1007/BF02328447
W. Wen-Tsün, Basic principles of mechanical theorem proving in elementary geometries, J. Autom. Reason. 2 (3) (1986) 221–252 · 1986
Earlier work this paper cites.
doi:10.1007/BF00283133
S. Chou, X. Gao, Automated generation of readable proofs with geometric invariants i. multiple and shortest proof generation, J. Autom. Reason. 17 (3) (1996) 325–347 · 1996
Earlier work this paper cites.
S. Hochreiter, J. Schmidhuber, Long short-term memory, Neural computation 9 (8) (1997) 1735–1780
1997
Earlier work this paper cites.
doi:10.1007/978-3-642-21046-4\_10
Z. Ye, S. Chou, X. Gao, An introduction to java geometry expert - (extended abstract), in: T. Sturm, C. Zengler (Eds.), Automated Deduction in Geometry - 7th International Workshop, ADG 2008, Shanghai, China, September 22-24, 2008. Revised Papers, Vol. 6301 of Lecture Notes in Computer Science, Springer, 2008, pp. 189–195 · 2008
Earlier work this paper cites.
O. Vinyals, M. Fortunato, N. Jaitly, Pointer networks , in: C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, R. Garnett (Eds.), Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, 2015, pp. 2692–2700. URL https://proceedings.neurips.cc/paper/2015/hash/29921001f2f04bd3baee84a12e98098f-Abstract.html
2015
Earlier work this paper cites.
D. P. Kingma, J. Ba, Adam: A method for stochastic optimization, in: Y. Bengio, Y. LeCun (Eds.), 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings, 2015
2015
Earlier work this paper cites.
doi:10.1109/CVPR.2016.90
K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, IEEE Computer Society, 2016, pp. 770–778 · 2016
Earlier work this paper cites.
doi:10.18653/v1/d17-1081
M. Sachan, A. Dubey, E. P. Xing, From textbooks to knowledge: A case study in harvesting axiomatic knowledge from textbooks to solve geometry problems, in: M. Palmer, R. Hwa, S. Riedel (Eds.), Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017, Copenhagen, Denmark, September 9-11, 2017, Association for Computational Linguistics, 2017, pp. 773–784 · 2017
Earlier work this paper cites.
doi:10.18653/v1/S17-1029
M. Sachan, E. P. Xing, Learning to solve geometry problems from natural language demonstrations in textbooks, in: N. Ide, A. Herbelot, L. Màrquez (Eds.), Proceedings of the 6th Joint Conference on Lexical and Computational Semantics, *SEM @ACM 2017, Vancouver, Canada, August 3-4, 2017, Association for Computational Linguistics, 2017, pp. 251–261 · 2017
Earlier work this paper cites.
C. Alvin, S. Gulwani, R. Majumdar, S. Mukhopadhyay, Synthesis of solutions for shaded area geometry problems, in: V. Rus, Z. Markov (Eds.), Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017, Marco Island, Florida, USA, May 22-24, 2017, AAAI Press, 2017, pp. 14–19
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, I. Polosukhin, Attention is all you need , in: I. Guyon, U. von Luxburg, S. Bengio, H. M. Wallach, R. Fergus, S. V. N. Vishwanathan, R. Garnett (Eds.), Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017, pp. 5998–6008. URL https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html
2017
Earlier work this paper cites.
A. Santoro, D. Raposo, D. G. T. Barrett, M. Malinowski, R. Pascanu, P. W. Battaglia, T. Lillicrap, A simple neural network module for relational reasoning, in: I. Guyon, U. von Luxburg, S. Bengio, H. M. Wallach, R. Fergus, S. V. N. Vishwanathan, R. Garnett (Eds.), Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 2017, pp. 4967–4976
2017
Cited alongside, same era.
E. Perez, F. Strub, H. de Vries, V. Dumoulin, A. C. Courville, Film: Visual reasoning with a general conditioning layer, in: S. A. McIlraith, K. Q. Weinberger (Eds.), Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018, AAAI Press, 2018, pp. 3942–3951
2018
Cited alongside, same era.
doi:10.18653/v1/n19-1245
A. Amini, S. Gabriel, S. Lin, R. Koncel-Kedziorski, Y. Choi, H. Hajishirzi, Mathqa: Towards interpretable math word problem solving with operation-based formalisms, in: J. Burstein, C. Doran, T. Solorio (Eds.), Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers), Association for Computational Linguistics, 2019, pp. 2357–2367 · 2019
S. Miao, C. Liang, K. Su, A diverse corpus for evaluating and developing english math word problem solvers, CoRR abs/2106.15772 (2021) · 2021
Later among the works it cites.
K. Cobbe, V. Kosaraju, M. Bavarian, J. Hilton, R. Nakano, C. Hesse, J. Schulman, Training verifiers to solve math word problems, CoRR abs/2110.14168 (2021) · 2021
Later among the works it cites.
J. Wei, X. Wang, D. Schuurmans, M. Bosma, E. H. Chi, Q. Le, D. Zhou, Chain of thought prompting elicits reasoning in large language models, CoRR abs/2201.11903 (2022) · 2022
Later among the works it cites.
doi:10.18653/v1/2022.acl-long.454
Y. Zhao, Y. Li, C. Li, R. Zhang, Multihiertt: Numerical reasoning over multi hierarchical tabular and textual data, in: S. Muresan, P. Nakov, A. Villavicencio (Eds.), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022, Dublin, Ireland, May 22-27, 2022, Association for Computational Linguistics, 2022, pp. 6588–6600 · 2022
Later among the works it cites.
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alphaXiv is searching for related work…
Cited alongside, same era.
doi:10.1109/CVPR.2019.00644
Z. Yu, J. Yu, Y. Cui, D. Tao, Q. Tian, Deep modular co-attention networks for visual question answering, in: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019, Computer Vision Foundation / IEEE, 2019, pp. 6281–6290 · 2019
Cited alongside, same era.
doi:10.18653/v1/n19-1423
J. Devlin, M. Chang, K. Lee, K. Toutanova, BERT: pre-training of deep bidirectional transformers for language understanding, in: J. Burstein, C. Doran, T. Solorio (Eds.), Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers), Association for Computational Linguistics, 2019, pp. 4171–4186 · 2019
Cited alongside, same era.
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, S. Chintala, Pytorch: An imperative style, high-performance deep learning library, in: Advances in Neural Information Processing Systems 32, Curran Associates, Inc., 2019, pp. 8024–8035
2019
Cited alongside, same era.
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, D. Amodei, Language models are few-shot learners, in: H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, H. Lin (Eds.), Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020
2020
Cited alongside, same era.
T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue, A. Moi, P. Cistac, T. Rault, R. Louf, M. Funtowicz, J. Davison, S. Shleifer, P. von Platen, C. Ma, Y. Jernite, J. Plu, C. Xu, T. L. Scao, S. Gugger, M. Drame, Q. Lhoest, A. M. Rush, Transformers: State-of-the-art natural language processing, in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Association for Computational Linguistics, Online, 2020, pp. 38–45
2020
Cited alongside, same era.
C. Raffel, N. Shazeer, A. Roberts, K. Lee, S. Narang, M. Matena, Y. Zhou, W. Li, P. J. Liu, Exploring the limits of transfer learning with a unified text-to-text transformer, J. Mach. Learn. Res. 21 (2020) 140:1–140:67
2020
Cited alongside, same era.
doi:10.18653/v1/2021.findings-acl.46
J. Chen, J. Tang, J. Qin, X. Liang, L. Liu, E. P. Xing, L. Lin, Geoqa: A geometric question answering benchmark towards multimodal numerical reasoning, in: C. Zong, F. Xia, W. Li, R. Navigli (Eds.), Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, Online Event, August 1-6, 2021, Vol. ACL/IJCNLP 2021 of Findings of ACL, Association for Computational Linguistics, 2021, pp. 513–523 · 2021
Cited alongside, same era.
doi:10.18653/v1/2021.acl-long.528
P. Lu, R. Gong, S. Jiang, L. Qiu, S. Huang, X. Liang, S. Zhu, Inter-gps: Interpretable geometry problem solving with formal language and symbolic reasoning, in: C. Zong, F. Xia, W. Li, R. Navigli (Eds.), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021, Association for Computational Linguistics, 2021, pp. 6774–6786 · 2021
Cited alongside, same era.
doi:10.18653/v1/2021.naacl-main.168
A. Patel, S. Bhattamishra, N. Goyal, Are NLP models really able to solve simple math word problems?, in: K. Toutanova, A. Rumshisky, L. Zettlemoyer, D. Hakkani-Tür, I. Beltagy, S. Bethard, R. Cotterell, T. Chakraborty, Y. Zhou (Eds.), Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, Online, June 6-11, 2021, Association for Computational Linguistics, 2021, pp. 2080–2094 · 2021
Cited alongside, same era.
J. Cao, J. Xiao, An augmented benchmark dataset for geometric question answering through dual parallel text encoding, in: N. Calzolari, C. Huang, H. Kim, J. Pustejovsky, L. Wanner, K. Choi, P. Ryu, H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, S. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics, COLING 2022, Gyeongju, Republic of Korea, October 12-17, 2022, International Committee on Computational Linguistics, 2022, pp. 1511–1520
2022
Later among the works it cites.
J. Chen, T. Li, J. Qin, P. Lu, L. Lin, C. Chen, X. Liang, Unigeo: Unifying geometry logical reasoning via reformulating mathematical expression, CoRR abs/2212.02746 (2022) · 2022
Later among the works it cites.
P. Lu, L. Qiu, K. Chang, Y. N. Wu, S. Zhu, T. Rajpurohit, P. Clark, A. Kalyan, Dynamic prompt learning via policy gradient for semi-structured mathematical reasoning, CoRR abs/2209.14610 (2022) · 2022
Later among the works it cites.
J. Zhang, Y. Moshfeghi, Elastic: Numerical reasoning with adaptive symbolic compiler, in: S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh (Eds.), Advances in Neural Information Processing Systems, Vol. 35, Curran Associates, Inc., 2022, pp. 12647–12661
2022
Later among the works it cites.
doi:10.24963/ijcai.2022/228
M. Zhang, F. Yin, Y. Hao, C. Liu, Plane geometry diagram parsing , in: L. D. Raedt (Ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI 2022, Vienna, Austria, 23-29 July 2022, ijcai.org, 2022, pp. 1636–1643 · 2022
Later among the works it cites.
M. Zhang, F. Yin, C. Liu, A multi-modal neural geometric solver with textual clauses parsed from diagram, CoRR abs/2302.11097 (2023) · 2023
Later among the works it cites.
doi:10.18653/v1/2023.findings-acl.850
S. Peng, D. Fu, Y. Liang, L. Gao, Z. Tang, Geodrl: A self-learning framework for geometry problem solving using reinforcement learning in deductive reasoning , in: A. Rogers, J. L. Boyd-Graber, N. Okazaki (Eds.), Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada, July 9-14, 2023, Association for Computational Linguistics, 2023, pp. 13468–13480 · 2023
Later among the works it cites.
M. Ning, Q. Wang, K. Huang, X. Huang, A symbolic character-aware model for solving geometry problems , CoRR abs/2308.02823 (2023) · 2023
Later among the works it cites.