7 citations · 18 across the 50 of their papers we have counts for
8 papers · 1 filter
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Dahyun Kim, Chanjun Park, Sanghoon Kim +15
We introduce SOLAR 10.7B, a large language model (LLM) with 10.7 billion parameters, demonstrating superior performance in various natural language processing (NLP) tasks. Inspired…
Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generation
Seugnjun Lee, Hyeonseok Moon, Chanjun Park +1
In this paper, we introduce a data-driven approach for Formality-Sensitive Machine Translation (FSMT) that caters to the unique linguistic properties of four target languages. Our…
Knowledge Graph-Augmented Korean Generative Commonsense Reasoning
Dahyun Jung, Jaehyung Seo, Jaewook Lee +2
Generative commonsense reasoning refers to the task of generating acceptable and logical assumptions about everyday situations based on commonsense understanding. By utilizing an e…
Synthetic Alone: Exploring the Dark Side of Synthetic Data for Grammatical Error Correction
Chanjun Park, Seonmin Koo, Seolhwa Lee +4
Data-centric AI approach aims to enhance the model performance without modifying the model and has been shown to impact model performance positively. While recent attention has bee…
Transcending Traditional Boundaries: Leveraging Inter-Annotator Agreement (IAA) for Enhancing Data Management Operations (DMOps)
Damrin Kim, NamHyeok Kim, Chanjun Park +1
This paper presents a novel approach of leveraging Inter-Annotator Agreement (IAA), traditionally used for assessing labeling consistency, to optimize Data Management Operations (D…
Inter-Annotator Agreement in the Wild: Uncovering Its Emerging Roles and Considerations in Real-World Scenarios
NamHyeok Kim, Chanjun Park
Inter-Annotator Agreement (IAA) is commonly used as a measure of label consistency in natural language processing tasks. However, in real-world scenarios, IAA has various roles and…
Self-Improving-Leaderboard(SIL): A Call for Real-World Centric Natural Language Processing Leaderboards
Chanjun Park, Hyeonseok Moon, Seolhwa Lee +3
Leaderboard systems allow researchers to objectively evaluate Natural Language Processing (NLP) models and are typically used to identify models that exhibit superior performance o…
DMOps: Data Management Operation and Recipes
Eujeong Choi, Chanjun Park
Data-centric AI has shed light on the significance of data within the machine learning (ML) pipeline. Recognizing its significance, academia, industry, and government departments h…