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Department of Computer Science and Engineering’s Data Intelligent and Learning Lab won the 5th AI Grand Challenge 2021.11.24
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Department of Computer Science and Engineering’s Data Intelligent and Learning Lab won the 5th AI Grand Challenge in 2021 



The Department of Computer Science and Engineering’s Data Intelligence and Leaning Lab (Adviser: Jong Wuk Lee) participated in the 5th – 2nd Phase of the 2021 AI Grand Challenge” and won the award. This contest was hosted by the Institute for Information & communication Technology Planning & evaluation (IITP) and 3 teams made to the final among 34 participating teams (228 people). The selected teams will be provided with 275 million KRW (total 1.425 billion KRW) worth of research fund to prepare for the 3rd phase of the contest.


The “AI Grand Challenge” is a challenging and competitive R&D competition in which participants compete for their skills using learning models developed to solve the presented problems. The 2nd phase of the 5th AI Grand Challenge was held from October 27 to 29 under the theme of “Use AI technology to solve descriptive math problems and present the solutions.”


Math Word Problem (MWP) aims to develop a learning model that presents solutions and answers in the form of formulas or programming for descriptive mathematical problems composed of natural languages. To this end, the learning model must be able to understand natural language sentences well, while being able to effectively generate the inter formulas for effectively solving math problems. Moreover, it can be said that it is an integrated body of advanced model must accept knowledge of various domains like humans and grasp the context of narrative problems and derive answers to formulas based on them.


The Data Intelligence and Leaning Lab won the 1st phase which was held in June, 2021 by developing a learning model that can effectively understand math problems in the form of natural language. In the 2nd phase, performance was improved by upgrading the model developed in the 1st phase and collecting additional data to solve more complex math problems.


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