2 citations · 4 across the 9 of their papers we have counts for
9 papers
RetroReasoner: A Reasoning LLM for Strategic Retrosynthesis Prediction
Hanbum Ko, Chanhui Lee, Ye Rin Kim +4
Retrosynthesis prediction aims to identify reactants that can synthesize a given product molecule. Although molecular large language models (LLMs) have recently shown promising res…
Machine Learning Hamiltonians are Accurate Energy-Force Predictors
Seongsu Kim, Chanhui Lee, Yoonho Kim +7
Recently, machine learning Hamiltonian (MLH) models have gained traction as fast approximations of electronic structures such as orbitals and electron densities, while also enablin…
Towards a Generalizable AI for Materials Discovery: Validation through Immersion Coolant Screening
Hyunseung Kim, Dae-Woong Jeong, Changyoung Park +11
Artificial intelligence (AI) has emerged as a powerful accelerator of materials discovery, yet most existing models remain problem-specific, requiring additional data collection an…
Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
Jiyeon Kang, Songseong Kim, Chanhui Lee +6
Ordering-based approaches to causal discovery identify topological orders of causal graphs, providing scalable alternatives to combinatorial search methods. Under the Additive Nois…
Mol-LLM: Multimodal Generalist Molecular LLM with Improved Graph Utilization
Chanhui Lee, Hanbum Ko, Yuheon Song +6
Recent advances in large language models (LLMs) have led to models that tackle diverse molecular tasks, such as chemical reaction prediction and molecular property prediction. Larg…
Scalable Multi-Task Transfer Learning for Molecular Property Prediction
Chanhui Lee, Dae-Woong Jeong, Sung Moon Ko +6
Molecules have a number of distinct properties whose importance and application vary. Often, in reality, labels for some properties are hard to achieve despite their practical impo…
Task Addition in Multi-Task Learning by Geometrical Alignment
Soorin Yim, Dae-Woong Jeong, Sung Moon Ko +4
Training deep learning models on limited data while maintaining generalization is one of the fundamental challenges in molecular property prediction. One effective solution is tran…
Multitask Extension of Geometrically Aligned Transfer Encoder
Sung Moon Ko, Sumin Lee, Dae-Woong Jeong +4
Molecular datasets often suffer from a lack of data. It is well-known that gathering data is difficult due to the complexity of experimentation or simulation involved. Here, we lev…
Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?
Chanhui Lee, Juhyeon Kim, Yongjun Jeong +9
Scaling laws have allowed Pre-trained Language Models (PLMs) into the field of causal reasoning. Causal reasoning of PLM relies solely on text-based descriptions, in contrast to ca…