7 citations · 9 across the 10 of their papers we have counts for
7 papers · 1 filter
LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models
Yungi Kim, Hyunsoo Ha, Seonghoon Yang +3
Creating high-quality, large-scale datasets for large language models (LLMs) often relies on resource-intensive, GPU-accelerated models for quality filtering, making the process ti…
Representing the Under-Represented: Cultural and Core Capability Benchmarks for Developing Thai Large Language Models
Dahyun Kim, Sukyung Lee, Yungi Kim +2
The rapid advancement of large language models (LLMs) has highlighted the need for robust evaluation frameworks that assess their core capabilities, such as reasoning, knowledge, a…
Open Ko-LLM Leaderboard2: Bridging Foundational and Practical Evaluation for Korean LLMs
Hyeonwoo Kim, Dahyun Kim, Jihoo Kim +3
The Open Ko-LLM Leaderboard has been instrumental in benchmarking Korean Large Language Models (LLMs), yet it has certain limitations. Notably, the disconnect between quantitative…
1 Trillion Token (1TT) Platform: A Novel Framework for Efficient Data Sharing and Compensation in Large Language Models
Chanjun Park, Hyunsoo Ha, Jihoo Kim +4
In this paper, we propose the 1 Trillion Token Platform (1TT Platform), a novel framework designed to facilitate efficient data sharing with a transparent and equitable profit-shar…
Rethinking KenLM: Good and Bad Model Ensembles for Efficient Text Quality Filtering in Large Web Corpora
Yungi Kim, Hyunsoo Ha, Sukyung Lee +3
With the increasing demand for substantial amounts of high-quality data to train large language models (LLMs), efficiently filtering large web corpora has become a critical challen…
Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark
Chanjun Park, Hyeonwoo Kim, Dahyun Kim +5
This paper introduces the Open Ko-LLM Leaderboard and the Ko-H5 Benchmark as vital tools for evaluating Large Language Models (LLMs) in Korean. Incorporating private test sets whil…
Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models
Hyunbyung Park, Sukyung Lee, Gyoungjin Gim +3
To address the challenges associated with data processing at scale, we propose Dataverse, a unified open-source Extract-Transform-Load (ETL) pipeline for large language models (LLM…