148 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Seoul National UniversityKR34 papers
- Sungkyunkwan UniversityKR17 papers
- Yonsei UniversityKR16 papers
- Korea UniversityKR15 papers
- Korea Institute for Advanced StudyKR14 papers
- University of PittsburghUS14 papers
- High Energy Accelerator Research OrganizationJP11 papers
- Kyungpook National UniversityKR11 papers
- Institute for Basic ScienceKR10 papers
- New Generation University CollegeET10 papers
- Tohoku UniversityJP10 papers
- Chonnam National UniversityKR9 papers
9 papers · 1 filter
TELLME: Test-Enhanced Learning for Language Model Enrichment
Minjun Kim, Inho Won, Hyeonseok Lim +6
Continual pre-training (CPT) has been widely adopted as a method for domain adaptation in large language models. However, CPT has consistently been accompanied by challenges, such…
LegiGPT: Party Politics and Transport Policy with Large Language Model
Hyunsoo Yun, Eun Hak Lee
Given the significant influence of lawmakers' political ideologies on legislative decision-making, analyzing their impact on transportation-related policymaking is of critical impo…
Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding
Yeonkyoung So, Gyuseong Lee, Sungmok Jung +4
Negation is a fundamental linguistic phenomenon that poses ongoing challenges for Large Language Models (LLMs), particularly in tasks requiring deep semantic understanding. Current…
X-LLaVA: Optimizing Bilingual Large Vision-Language Alignment
Dongjae Shin, Hyeonseok Lim, Inho Won +6
The impressive development of large language models (LLMs) is expanding into the realm of large multimodal models (LMMs), which incorporate multiple types of data beyond text. Howe…
BOK-VQA: Bilingual outside Knowledge-Based Visual Question Answering via Graph Representation Pretraining
Minjun Kim, Seungwoo Song, Youhan Lee +2
The current research direction in generative models, such as the recently developed GPT4, aims to find relevant knowledge information for multimodal and multilingual inputs to prov…
Korean Named Entity Recognition Based on Language-Specific Features
Yige Chen, KyungTae Lim, Jungyeul Park
In the paper, we propose a novel way of improving named entity recognition in the Korean language using its language-specific features. While the field of named entity recognition…
ALBERT with Knowledge Graph Encoder Utilizing Semantic Similarity for Commonsense Question Answering
Byeongmin Choi, YongHyun Lee, Yeunwoong Kyung +1
Recently, pre-trained language representation models such as bidirectional encoder representations from transformers (BERT) have been performing well in commonsense question answer…
Abstractive Summarization of Reddit Posts with Multi-level Memory Networks
Byeongchang Kim, Hyunwoo Kim, Gunhee Kim
We address the problem of abstractive summarization in two directions: proposing a novel dataset and a new model. First, we collect Reddit TIFU dataset, consisting of 120K posts fr…
What we really want to find by Sentiment Analysis: The Relationship between Computational Models and Psychological State
Hwiyeol Jo, Soo-Min Kim, Jeong Ryu
As the first step to model emotional state of a person, we build sentiment analysis models with existing deep neural network algorithms and compare the models with psychological me…