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 such as English, instruction-based datasets are being constructed and made publicly available. In the case of Korean, publicly available models and datasets all rely on using the output of ChatGPT or translating datasets built in English. In this paper, We introduce KIT-19 as an instruction dataset for the development of LLM in Korean. KIT-19 is a dataset created in an instruction format, comprising 19 existing open-source datasets for Korean NLP tasks. In this paper, we train a Korean Pretrained LLM using KIT-19 to demonstrate its effectiveness. The experimental results show that the model trained on KIT-19 significantly outperforms existing Korean LLMs. Based on the its quality and empirical results, this paper proposes that KIT-19 has the potential to make a substantial contribution to the future improvement of Korean LLMs' performance.
Orchidaceous plants have symbiotic relationships with endophytic fungi, including mycorrhizal fungi, which play important roles in the seed germination and growth of the host plants. In this study, endophytic fungal communities isolated from the roots of Cephalanthera longibracteata collected from three different sites in Korea were analyzed, and it was determined whether fungal communities were preferentially correlated with the sites. The fungal isolates were identified by sequence analysis of the internal transcribed spacer regions of rDNA. In total, 30 species of endophytic fungi, including two species of mycorrhizal fungi belonging to the genus Tulasnella, were identified. Leptodontidium orchidicola showed the highest frequency and was isolated from all root samples. Species diversity and richness were not significantly different among sites. However, the community structure of the endophytic fungi significantly differed among sites, suggesting that the site characteristics affected the community composition of the endophytic fungi colonizing the roots of C. longibracteata. Our findings will aid in developing methods involving the use of symbiotic fungi for orchid conservation and restoration in native habitats.
Diverse endophytic fungi were isolated from surface-sterilized leaves of three species of conifers inhabiting various sites in Korea: Abies nephrolepis, Pinus koraiensis and Taxus cuspidate. The isolates were identified based on morphological characteristics and sequences analysis of both internal transcribed spacer and large subunit regions of rDNA. In this paper, we report on five previously unreported species of endophytic fungi isolated from conifers: Biscogniauxia maritime, Nemania diffusa, Pezicula carpinea, Phomopsis juglandina and Sydowia polyspora.
In this study, endophytic fungi were isolated from leaves of four species of woody plants, Acer tagmentosum, Larix kaempferi, Abies holophylla, and Pinus koraiensis, on Mt. Hambaek, Gangwondo, Korea. The endophytic fungi were identified using morphological and sequences analysis of ITS regions. The fungal endophytes were identified as Talaromyces radicus, Myceliophthora verrucosa, Cryptosporiopsis diversispora, and Sphaerulina berberidis, which are the first record in Korea. The morphological and molecular phylogenetic characteristics of each strain were described.
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