Search Results for author: EungGyun Kim

Found 7 papers, 2 papers with code

RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases

1 code implementation CL (ACL) 2021 DongHyun Choi, Myeong Cheol Shin, EungGyun Kim, Dong Ryeol Shin

Text-to-SQL is the problem of converting a user question into an SQL query, when the question and database are given.

Ranked #7 on Text-To-SQL on spider (Exact Match Accuracy (Test) metric)

Position slot-filling +2

OutFlip: Generating Out-of-Domain Samples for Unknown Intent Detection with Natural Language Attack

1 code implementation12 May 2021 DongHyun Choi, Myeong Cheol Shin, EungGyun Kim, Dong Ryeol Shin

Out-of-domain (OOD) input detection is vital in a task-oriented dialogue system since the acceptance of unsupported inputs could lead to an incorrect response of the system.

intent-classification Intent Classification +1

Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization

no code implementations COLING 2020 Dongyub Lee, Myeongcheol Shin, Taesun Whang, Seungwoo Cho, Byeongil Ko, Daniel Lee, EungGyun Kim, Jaechoon Jo

In this paper, we propose evaluation metrics that reflect semantic meanings of a reference summary and the original document, Reference and Document Aware Semantic Score (RDASS).

Text Summarization

Auxiliary Sequence Labeling Tasks for Disfluency Detection

no code implementations24 Oct 2020 Dongyub Lee, Byeongil Ko, Myeong Cheol Shin, Taesun Whang, Daniel Lee, Eun Hwa Kim, EungGyun Kim, Jaechoon Jo

Existing works for disfluency detection have focused on designing a single objective only for disfluency detection, while auxiliary objectives utilizing linguistic information of a word such as named entity or part-of-speech information can be effective.

named-entity-recognition Named Entity Recognition +4

Deep Context- and Relation-Aware Learning for Aspect-based Sentiment Analysis

no code implementations ACL 2021 Shinhyeok Oh, Dongyub Lee, Taesun Whang, IlNam Park, Gaeun Seo, EungGyun Kim, Harksoo Kim

In this paper, we propose Deep Contextualized Relation-Aware Network (DCRAN), which allows interactive relations among subtasks with deep contextual information based on two modules (i. e., Aspect and Opinion Propagation and Explicit Self-Supervised Strategies).

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1

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