most citedCS1QA: A Dataset for Assisting Code-based Question Answering in an Introductory Programming Course

10 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL202210 cited

CS1QA: A Dataset for Assisting Code-based Question Answering in an Introductory Programming Course

Changyoon Lee, Yeon Seonwoo, Alice Oh

We introduce CS1QA, a dataset for code-based question answering in the programming education domain. CS1QA consists of 9,237 question-answer pairs gathered from chat logs in an int…

cs.CL2022

IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension

Rifki Afina Putri, Alice Oh

Machine Reading Comprehension (MRC) has become one of the essential tasks in Natural Language Understanding (NLU) as it is often included in several NLU benchmarks (Liang et al., 2…

cs.CL20227 cited

HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea

Haneul Yoo, Jiho Jin, Juhee Son +3

Historical records in Korea before the 20th century were primarily written in Hanja, an extinct language based on Chinese characters and not understood by modern Korean or Chinese…

cs.LG2022

Models and Benchmarks for Representation Learning of Partially Observed Subgraphs

Dongkwan Kim, Jiho Jin, Jaimeen Ahn +1

Subgraphs are rich substructures in graphs, and their nodes and edges can be partially observed in real-world tasks. Under partial observation, existing node- or subgraph-level mes…

cs.CL2022

Two-Step Question Retrieval for Open-Domain QA

Yeon Seonwoo, Juhee Son, Jiho Jin +4

The retriever-reader pipeline has shown promising performance in open-domain QA but suffers from a very slow inference speed. Recently proposed question retrieval models tackle thi…

cs.CL2021

Efficient Contrastive Learning via Novel Data Augmentation and Curriculum Learning

Seonghyeon Ye, Jiseon Kim, Alice Oh

We introduce EfficientCL, a memory-efficient continual pretraining method that applies contrastive learning with novel data augmentation and curriculum learning. For data augmentat…