no code implementations • Findings (EMNLP) 2021 • HyeonTae Seo, Yo-Sub Han, Sang-Ki Ko
We consider the problem of learning to repair erroneous C programs by learning optimal alignments with correct programs.
1 code implementation • 14 Jun 2023 • Hyunsung Kim, Han-Jun Choi, Chang Jo Kim, Jinsung Yoon, Sang-Ki Ko
As artificial intelligence spreads out to numerous fields, the application of AI to sports analytics is also in the spotlight.
1 code implementation • 22 Jun 2022 • Hyunsung Kim, Bit Kim, Dongwook Chung, Jinsung Yoon, Sang-Ki Ko
In fluid team sports such as soccer and basketball, analyzing team formation is one of the most intuitive ways to understand tactics from domain participants' point of view.
no code implementations • 20 May 2022 • Su-Hyeon Kim, Hyunjoon Cheon, Yo-Sub Han, Sang-Ki Ko
We tackle the problem of learning regexes faster from positive and negative strings by relying on a novel approach called `neural example splitting'.
no code implementations • 29 Sep 2021 • Su-Hyeon Kim, Hyunjoon Cheon, Yo-Sub Han, Sang-Ki Ko
SplitRegex is a divided-and-conquer framework for learning target regexes; split (=divide) positive strings and infer partial regexes for multiple parts, which is much more accurate than the whole string inferring, and concatenate (=conquer) inferred regexes while satisfying negative strings.
no code implementations • 10 Sep 2021 • Hyunsung Kim, Jihun Kim, Dongwook Chung, Jonghyun Lee, Jinsung Yoon, Sang-Ki Ko
Although the values of individual soccer players have become astronomical, subjective judgments still play a big part in the player analysis.
no code implementations • IJCNLP 2019 • Jun-U Park, Sang-Ki Ko, Marco Cognetta, Yo-Sub Han
We continue the study of generating se-mantically correct regular expressions from natural language descriptions (NL).
no code implementations • 28 Nov 2018 • Sang-Ki Ko, Chang Jo Kim, Hyedong Jung, Choongsang Cho
Using the KETI sign language dataset, we develop a neural network model for translating sign videos into natural language sentences by utilizing the human keypoints extracted from a face, hands, and body parts.