1 code implementation • ACL 2022 • Bugeun Kim, Kyung Seo Ki, Sangkyu Rhim, Gahgene Gweon
(1) EPT-X model: An explainable neural model that sets a baseline for algebraic word problem solving task, in terms of model’s correctness, plausibility, and faithfulness.
Ranked #1 on Math Word Problem Solving on PEN
1 code implementation • EMNLP 2020 • Bugeun Kim, Kyung Seo Ki, Donggeon Lee, Gahgene Gweon
The contribution of this paper is two-fold; (1) We propose a pure neural model, EPT, which can address the expression fragmentation and the operand-context separation.
Ranked #3 on Math Word Problem Solving on DRAW-1K
no code implementations • COLING 2020 • Kyung Seo Ki, Donggeon Lee, Bugeun Kim, Gahgene Gweon
In this paper, we propose the GEO (Generation of Equations by utilizing Operators) model that does not use hand-crafted features and addresses two issues that are present in existing neural models: 1. missing domain-specific knowledge features and 2. losing encoder-level knowledge.
Ranked #2 on Math Word Problem Solving on DRAW-1K