most citedA Study on How Attention Scores in the BERT Model are Aware of Lexical Categories in Syntactic and Semantic Tasks on the GLUE Benchmark

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2025

KoBALT: Korean Benchmark For Advanced Linguistic Tasks

Hyopil Shin, Sangah Lee, Dongjun Jang +9

We introduce KoBALT (Korean Benchmark for Advanced Linguistic Tasks), a comprehensive linguistically-motivated benchmark comprising 700 multiple-choice questions spanning 24 phenom…

cs.CL20241 cited

DAHL: Domain-specific Automated Hallucination Evaluation of Long-Form Text through a Benchmark Dataset in Biomedicine

Jean Seo, Jongwon Lim, Dongjun Jang +1

We introduce DAHL, a benchmark dataset and automated evaluation system designed to assess hallucination in long-form text generation, specifically within the biomedical domain. Our…

cs.CL20241 cited

A Study on How Attention Scores in the BERT Model are Aware of Lexical Categories in Syntactic and Semantic Tasks on the GLUE Benchmark

Dongjun Jang, Sungjoo Byun, Hyopil Shin

This study examines whether the attention scores between tokens in the BERT model significantly vary based on lexical categories during the fine-tuning process for downstream tasks…

cs.CL2024

KIT-19: A Comprehensive Korean Instruction Toolkit on 19 Tasks for Fine-Tuning Korean Large Language Models

Dongjun Jang, Sungjoo Byun, Hyemi Jo +1

Instruction Tuning on Large Language Models is an essential process for model to function well and achieve high performance in specific tasks. Accordingly, in mainstream languages…

cs.CL2024

Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition

Sungjoo Byun, Jiseung Hong, Sumin Park +5

Named Entity Recognition (NER) plays a pivotal role in medical Natural Language Processing (NLP). Yet, there has not been an open-source medical NER dataset specifically for the Ko…

cs.CL2024

CARBD-Ko: A Contextually Annotated Review Benchmark Dataset for Aspect-Level Sentiment Classification in Korean

Dongjun Jang, Jean Seo, Sungjoo Byun +3

This paper explores the challenges posed by aspect-based sentiment classification (ABSC) within pretrained language models (PLMs), with a particular focus on contextualization and…