Semantically-Aligned Universal Tree-Structured Solver for Math
November 16–20 2020. c 2020 Association for Computational Linguistics. 3780. Semantically-Aligned Universal Tree-Structured Solver for Math Word. Problems.
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Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks
1 août 2021 MWP solving aims to automatically answer a math word prob- lem by understanding the textual description of the problem and reasoning out the ...
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Recall and Learn: A Memory-augmented Solver for Math Word
7 nov. 2021 solving math word problems in a recall and learn man- ner. by the proliferation of deep learning techniques. Seq2Seq-based models have been ...
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Deep Neural Solver for Math Word Problems
7 sept. 2017 solve math word problems has been an interest of NLP researchers since 1963 Feigenbaum ... for automatic math word problem solving. It is a.
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Seeking Patterns Not just Memorizing Procedures: Contrastive
22 mai 2022 Contrastive Learning for Solving Math Word Problems. Zhongli Li1∗ Wenxuan Zhang2∗†
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Explanation Generation for a Math Word Problem Solver
oriented approach to explain how the answers are obtained for math word problems. Based on the reasoning chain given by the inference engine we search each
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Solving Math Word Problems with Teacher Supervision
when a delicate variation is applied to the word ex- pression of a math problem and leads to a remark- ably different answer. We find the failure is
A Goal-Driven Tree-Structured Neural Model for Math Word Problems
Next the same process is re- peated for each sub-goal until all goals get realized. As for the example shown in Table 1
HMS: A Hierarchical Solver with Dependency-Enhanced
Automatically solving math word problems is a crucial task for exploring the intelligence levels of machines in the gen- eral AI domain.
Are NLP Models really able to Solve Simple Math Word Problems?
Since existing solvers achieve high performance on the benchmark datasets for elementary level MWPs contain- ing one-unknown arithmetic word problems such
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