3 papers
cond-mat.mtrl-sci2025
Atomistic Insights into Cu/amorphous-TaN Interfacial Adhesion via Machine Learning Interatomic Potentials: Effects of Stoichiometry and Interface Construction
Jeong Min Choi, Jaehoon Kim, Ji-Hwan Lee +2
Accurate understanding and control of interfacial adhesion between Cu and TaN diffusion barriers are essential for ensuring the mechanical reliability and integrity of Cu inter…
cs.LG2025
Contextually Guided Transformers via Low-Rank Adaptation
Andrey Zhmoginov, Jihwan Lee, Max Vladymyrov +1
Large Language Models (LLMs) based on Transformers excel at text processing, but their reliance on prompts for specialized behavior introduces computational overhead. We propose a…
cs.LG2025
Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones
Andrey Zhmoginov, Jihwan Lee, Mark Sandler
Modern Foundation Models (FMs) are typically trained on corpora spanning a wide range of different data modalities, topics and downstream tasks. Utilizing these models can be very…