Search Results for author: Chao-Chun Liang

Found 10 papers, 3 papers with code

A Flexible and Extensible Framework for Multiple Answer Modes Question Answering

no code implementations ROCLING 2021 Cheng-Chung Fan, Chia-Chih Kuo, Shang-Bao Luo, Pei-Jun Liao, Kuang-Yu Chang, Chiao-Wei Hsu, Meng-Tse Wu, Shih-Hong Tsai, Tzu-Man Wu, Aleksandra Smolka, Chao-Chun Liang, Hsin-Min Wang, Kuan-Yu Chen, Yu Tsao, Keh-Yih Su

Only a few of them adopt several answer generation modules for providing different mechanisms; however, they either lack an aggregation mechanism to merge the answers from various modules, or are too complicated to be implemented with neural networks.

Answer Generation Question Answering

Mining Commonsense and Domain Knowledge from Math Word Problems

no code implementations ROCLING 2021 Shih-hung Tsai, Chao-Chun Liang, Hsin-Min Wang, Keh-Yih Su

We construct two math datasets and show the effectiveness of our algorithms that they can retrieve the required knowledge for problem-solving.


A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers

1 code implementation ACL 2020 Shen-yun Miao, Chao-Chun Liang, Keh-Yih Su

We present ASDiv (Academia Sinica Diverse MWP Dataset), a diverse (in terms of both language patterns and problem types) English math word problem (MWP) corpus for evaluating the capability of various MWP solvers.


Answering Chinese Elementary School Social Study Multiple Choice Questions

no code implementations26 Jun 2021 Daniel Lee, Chao-Chun Liang, Keh-Yih Su

We present a novel approach to answer the Chinese elementary school Social Study Multiple Choice questions.

Multiple-choice Negation +1

Sequence to General Tree: Knowledge-Guided Geometry Word Problem Solving

1 code implementation ACL 2021 Shih-hung Tsai, Chao-Chun Liang, Hsin-Min Wang, Keh-Yih Su

With the recent advancements in deep learning, neural solvers have gained promising results in solving math word problems.


A Meaning-based Statistical English Math Word Problem Solver

1 code implementation NAACL 2018 Chao-Chun Liang, Yu-Shiang Wong, Yi-Chung Lin, Keh-Yih Su

We introduce MeSys, a meaning-based approach, for solving English math word problems (MWPs) via understanding and reasoning in this paper.


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