51 citations · 65 across the 23 of their papers we have counts for
7 papers · 1 filter
How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?
Tuan Anh Tran, Duy M. H. Nguyen, Hoai-Chau Tran +7
Recent advances in 3D point cloud transformers have led to state-of-the-art results in tasks such as semantic segmentation and reconstruction. However, these models typically rely…
S-Chain: Structured Visual Chain-of-Thought For Medicine
Khai Le-Duc, Duy M. H. Nguyen, Phuong T. H. Trinh +21
Faithful reasoning in medical vision-language models (VLMs) requires not only accurate predictions but also transparent alignment between textual rationales and visual evidence. Wh…
Performance of universal machine-learned potentials with explicit long-range interactions in biomolecular simulations
Viktor Zaverkin, Matheus Ferraz, Francesco Alesiani +1
Universal machine-learned potentials promise transferable accuracy across compositional and vibrational degrees of freedom, yet their application to biomolecular simulations remain…
Adaptive Transition State Refinement with Learned Equilibrium Flows
Samir Darouich, Vinh Tong, Tanja Bien +2
Identifying transition states (TSs), the high-energy configurations that molecules pass through during chemical reactions, is essential for understanding and designing chemical pro…
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca +9
While machine learning on graphs has demonstrated promise in drug design and molecular property prediction, significant benchmarking challenges hinder its further progress and rele…
On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation
Nghiem T. Diep, Huy Nguyen, Chau Nguyen +5
The LLaMA-Adapter has recently emerged as an efficient fine-tuning technique for LLaMA models, leveraging zero-initialized attention to stabilize training and enhance performance.…
Adaptive Width Neural Networks
Federico Errica, Henrik Christiansen, Viktor Zaverkin +2
For almost 70 years, researchers have typically selected the width of neural networks' layers either manually or through automated hyperparameter tuning methods such as grid search…