Yuxuan Hu


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A Generation-based Deductive Method for Math Word Problems
Yuxuan Hu | Jing Zhang | Haoyang Li | Cuiping Li | Hong Chen
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Math word problems (MWP) involving advanced operators such as linear equation solver cannot be easily tackled by earlier MWP methods, because the existing generation methods suffer from repeated sub-expression generation and deductive methods are restricted to dealing with binary operations. This paper propose a new multivariate directed acyclic graph (mDAG) as an alternative to the generation methods’ binary expression tree or the deductive methods’ binary directed acyclic graph. Then to produce the topological ordering of mDAG, we propose a generation-based deductive (GeDe) model, which equips a generation model with a re-encoder to keep the deductive property but avoid the expensive enumeration of the deductive methods. GeDe performs well on math problems with many operators on the widely used benchmarks as well as solving multivariate operators on our own CMWPA benchmark. Our code is available at https://github.com/hyx1999/GeDe


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A Cascaded Syntactic and Semantic Dependency Parsing System
Wanxiang Che | Zhenghua Li | Yuxuan Hu | Yongqiang Li | Bing Qin | Ting Liu | Sheng Li
CoNLL 2008: Proceedings of the Twelfth Conference on Computational Natural Language Learning


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HIT-IR-WSD: A WSD System for English Lexical Sample Task
Yuhang Guo | Wanxiang Che | Yuxuan Hu | Wei Zhang | Ting Liu
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)


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Semantic Role Labeling System Using Maximum Entropy Classifier
Ting Liu | Wanxiang Che | Sheng Li | Yuxuan Hu | Huaijun Liu
Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)