51 citations · 65 across the 23 of their papers we have counts for
6 papers · 1 filter
ExGra-Med: Extended Context Graph Alignment for Medical Vision-Language Models
Duy M. H. Nguyen, Nghiem T. Diep, Trung Q. Nguyen +10
State-of-the-art medical multi-modal LLMs (med-MLLMs), such as LLaVA-Med and BioMedGPT, primarily depend on scaling model size and data volume, with training driven largely by auto…
Physics-Informed Weakly Supervised Learning for Interatomic Potentials
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
Machine learning plays an increasingly important role in computational chemistry and materials science, complementing computationally intensive ab initio and first-principles metho…
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model
Duy M. H. Nguyen, An T. Le, Trung Q. Nguyen +7
Prompt learning methods are gaining increasing attention due to their ability to customize large vision-language models to new domains using pre-trained contextual knowledge and mi…
Accelerating Transformers with Spectrum-Preserving Token Merging
Hoai-Chau Tran, Duy M. H. Nguyen, Duy M. Nguyen +7
Increasing the throughput of the Transformer architecture, a foundational component used in numerous state-of-the-art models for vision and language tasks (e.g., GPT, LLaVa), is an…
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama +5
The ability to perform fast and accurate atomistic simulations is crucial for advancing the chemical sciences. By learning from high-quality data, machine-learned interatomic poten…
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
Duy M. H. Nguyen, Nina Lukashina, Tai Nguyen +7
A molecule's 2D representation consists of its atoms, their attributes, and the molecule's covalent bonds. A 3D (geometric) representation of a molecule is called a conformer and c…