Multimodal Language Processing Lab.
KAIST 멀티모달 자연어처리 연구실 (임경태 교수와 MLP랩)
https://sites.google.com/view/aailab
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News
News
(2026, Jan.) Our paper "Enriching the Korean learner corpus for grammatical error correction and writing assessment", is accepted to Language Resources and Evaluation (SCIE)
(2026, Jan.) Four papers are accepted to EACL2026
(2025, Aug.) Our laboratory has been selected for the "우수신진" research project (NRF)
(2025, Aug.) Two papers are accepted to EMNLP2025
(2025, Aug.) Our laboratory has been selected for the "독자 AI파운데이션 모델 프로젝트" research project with Upstage (IITP)
(2025, July.) Our laboratory has been selected for the "생성AI 선도인재양성 사업" research project with NC AI (IITP)
(2025, July.) Our laboratory has been selected for the "AI 글로벌 빅테크 육성사업" research project with KAERI (IITP)
(2025, Feb.) Two papers are accepted to NAACL 2025
(2025, Jan.) Two papers are accepted to COLING 2025
(2025, Jan.) Our paper Integrating Econometrics and Artificial Intelligence to Access the Impact of Trade on Nuclear Proliferation, is accepted to Nuclear Technology (SCIE)
Research
KAIST 멀티모달 언어처리 연구실(MLP Lab)은 (1) 한국어 언어자원 설계 (2) 전통 자연어처리 (3) 멀티모달 초거대 언어모델을 연구합니다
Large Language Model (LLM) & dataset
Large Language Model (LLM) & dataset
KORMo and Bllossom: Building and Scaling the First Korean–English 10B-Scale Foundation Models from Scratch in an Academic Lab
Research and dissemination of fully open-source Korean LLMs
Efficient bilingual tokenizer design and analysis
Observing pre-training performance across diverse data composition strategies
Domain-specialized vision–language models
Knowledge transfer using agent-style teacher models
https://huggingface.co/KORMo-Team
Large Language Model (LLM) & dataset based on Linguistic features
Large Language Model (LLM) & dataset based on Linguistic features
Lead of the Bllossom project. (https://www.bllossom.ai) (https://huggingface.co/MLP-KTLim/llama-3-Korean-Bllossom-8B)
Lead of the Universal Korean Language Resource project. (https://sites.google.com/view/universal-korean)
Visual language model & Video Story Understanding
Visual language model & Video Story Understanding
Visual Question Answering (VQA) is a question answering system that answers user's questions based on the input image and question.
Bllossom-V: Vision-Language Model
Bllossom-V: Vision-Language Model
What we have done (KBVQA Chatbot)
What we have done (KBVQA Chatbot)
Applied Artificial Intelligence on Robotics
Applied Artificial Intelligence on Robotics
Vision-Language-Action Model
Control of Robots Based on Speech Teaching Command
Nvidia Jetson Nano, Jet Racer, Jet racer pro
Spot (Boston Dynamics)
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