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X-WR-CALNAME:Biomedical Mathematics Group
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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TZID:Asia/Seoul
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TZOFFSETFROM:+0900
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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Seoul:20260210T160000
DTEND;TZID=Asia/Seoul:20260210T180000
DTSTAMP:20260430T214740
CREATED:20260126T084409Z
LAST-MODIFIED:20260126T084537Z
UID:12148-1770739200-1770746400@www.ibs.re.kr
SUMMARY:Toward a Foundation Model for Molecular Tasks - Sungbin Lim
DESCRIPTION:Abstract \n(국문) 최근 거대언어모델(LLM)을 기술의 발전은 AI4Science 분야에서 Foundation Model 개발에 대한 세계적인 관심을 촉발하였다. 그 중에서도 신약 및 신소재 개발에 연계된 Molecular 도메인에서의 Foundation Model 연구는 막대한 산업적 영향력과 가치를 가지고 있다. 본 발표에서는 분자 구조 생성\, 물성\, 및 반응 예측 문제에 적용되기 위해 필요한 Multimodal LLM 연구 성과와 방향성을 소개하고자 한다. \n(English) The advancement of Large Language Models (LLMs) is drawing huge interest in developing Foundation Models for the field of AI4Science. In particular\,  Foundation Model research within the molecular domain\, specifically linked to drug discovery and advanced materials\, holds immense industrial impact and value. In this presentation\, we introduce recent achievements in Multimodal LLM research for molecular structure generation\, property prediction\, and chemical reaction forecasting. This is a joint work with LG AI Research.
URL:https://www.ibs.re.kr/bimag/event/toward-a-foundation-model-for-molecular-tasks-sungbin-lim/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
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