7 citations · 7 across the 6 of their papers we have counts for
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cs.CL2024
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…
cs.CL2024
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…
cs.CL2024
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…