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| title: README | |
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| ### KONI: KISTI Open Neural Intelligence | |
| KONI refers to large language models (LLMs) and LLM-based technologies developed by the Large-scale AI Research Center at KISTI (Korea Institute of Science and Technology Information), with a focus on developing and sharing Korean language models, datasets, and AI for Science technologies. | |
| Our contributions include various language models and datasets designed to advance Korean natural language processing (NLP) techniques and to utilize science and technology information. | |
| By providing these resources, KONI aims to help researchers and developers create AI-based applications that effectively understand, analyze, and generate Korean scientific texts, thereby contributing to the realization of the vision of AI for Science. | |
| We are also maintaining our GitHub page: https://github.com/KISTI-KONI | |
| ### NEWS | |
| - [2025.08.31] The reasoning model KONI-R 7B,8B models released, collaborated with OnelineAI, HAERAE, and Oracle. | |
| - [2025.08.29] We are excited to introduce DOREA (Document Oriented Reasoning and Explanation Assistant)! | |
| DOREA is an AI assistant currently under development with the goal of intelligently understanding and answering questions about PDF documents. | |
| It is designed to recognize and process text, images, and tables within documents, enabling interactive services such as translation, summarization, and analysis powered by LLMs. | |
| In addition, through its Retrieval-Augmented Generation (RAG) capabilities, DOREA will provide efficient search and question-answering over your own documents, making document-centric workflows more productive and seamless. https://lnkd.in/gzFpjUhB | |
| - [2025.08.22] We’re also releasing SpectraBench, a benchmark suite that lets you evaluate across 25+ LLM benchmarks all at once, with an intelligent scheduling facility https://lnkd.in/g7eBEKkU | |
| - [2025.08.22] We’re open-sourcing the MCP Server code that connects to KISTI’s public services, ScienceON and NTIS, to help turn that data into AI-powered agents. https://lnkd.in/g8Y9DP_a | |
| - [2025.08.22] KONI 4B base model released, better overall performance than KONI-Llama3.1-8b-Instruct at half the size. | |
| - [2025.05.20] "ScholarBench: A Bilingual Benchmark for Abstraction, Comprehension, and Reasoning Evaluation in Academic Contexts" is now publicly available. | |
| - [2025.03.20] (Preview) KONI-Llama3.1-8B-R model released (specialized for reasoning tasks). | |
| - [2025.03.17] KONI was introduced at the Meta Innovation Hub as a representative example of Korea's digital transformation utilizing Llama in the public sector. (https://about.meta.com/apacinnovationhub/ai-for-organizations) | |
| - [2024.12.10] ScienceON will begin providing an AI-reviewer service using KONI LLM that provides various analysis functions including understanding multiple scientific papers at once, comparing papers, summarizing papers, identifying limitations and differences, and conducting free Q&As. Please visit ScienceON to check how it works (https://scienceon.kisti.re.kr). | |
| - [2024.11.15] KONI-Llama3.1-70B-Instruct model released with LogicKor Benchmark Score 9.38/10. | |
| - [2024.10.31] KONI LLM has been used to paper summarization service in AccessON, the Open Access Journal Repository. Visit AccessON to see how it works(https://accesson.kisti.re.kr) | |
| - [2024.10.24] KONI-Llama3.1-8B-Instruct model released with LogicKor Benchmark Score 8.93/10. | |
| - [2024.07.29] KONI-Llama3-8B-Instruct model released with LogicKor Benchmark Score 8.21/10. | |
| # If you have any question about KONI, please contact to {kyongha, yangdonghun3}@kisti.re.kr | |