Search Results for author:
Found 18 papers, 1 papers with code
The Korean Morphologically Tight-Fitting Tokenizer for Noisy User-Generated Texts
User-generated texts include various types of stylistic properties, or noises.
Generating Slogans with Linguistic Features using Sequence-to-Sequence Transformer
We present LexPOS, a sequence-to-sequence transformer model that generates slogans given phonetic and structural information.
KIT-19: A Comprehensive Korean Instruction Toolkit on 19 Tasks for Fine-Tuning Korean Large Language Models
Based on the its quality and empirical results, this paper proposes that \textit{KIT-19} has the potential to make a substantial contribution to the future improvement of Korean LLMs' performance.
A Study on How Attention Scores in the BERT Model are Aware of Lexical Categories in Syntactic and Semantic Tasks on the GLUE Benchmark
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.
Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition
Named Entity Recognition (NER) plays a pivotal role in medical Natural Language Processing (NLP).
Medical Named Entity Recognition
named-entity-recognition
+2
CARBD-Ko: A Contextually Annotated Review Benchmark Dataset for Aspect-Level Sentiment Classification in Korean
In order to tackle these challenges, we introduce CARBD-Ko (a Contextually Annotated Review Benchmark Dataset for Aspect-Based Sentiment Classification in Korean), a benchmark dataset that incorporates aspects and dual-tagged polarities to distinguish between aspect-specific and aspect-agnostic sentiment classification.
Automatic Construction of a Korean Toxic Instruction Dataset for Ethical Tuning of Large Language Models
Caution: this paper may include material that could be offensive or distressing.
DaG LLM ver 1.0: Pioneering Instruction-Tuned Language Modeling for Korean NLP
This paper presents the DaG LLM (David and Goliath Large Language Model), a language model specialized for Korean and fine-tuned through Instruction Tuning across 41 tasks within 13 distinct categories.
KR-BERT: A Small-Scale Korean-Specific Language Model
Since the appearance of BERT, recent works including XLNet and RoBERTa utilize sentence embedding models pre-trained by large corpora and a large number of parameters.
A New Approach for Measuring Sentiment Orientation based on Multi-Dimensional Vector Space
This study implements a vector space model approach to measure the sentiment orientations of words.
