6 papers
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…
DoRAN: Stabilizing Weight-Decomposed Low-Rank Adaptation via Noise Injection and Auxiliary Networks
Nghiem T. Diep, Hien Dang, Tuan Truong +3
Parameter-efficient fine-tuning (PEFT) methods have become the standard paradigm for adapting large-scale models. Among these techniques, Weight-Decomposed Low-Rank Adaptation (DoR…
Hypernetwork-Driven Low-Rank Adaptation Across Attention Heads
Nghiem T. Diep, Dung Le, Tuan Truong +3
Parameter-efficient fine-tuning (PEFT) has emerged as a powerful paradigm for adapting large-scale pre-trained models to downstream tasks with minimal additional parameters. Among…
MELCOT: A Hybrid Learning Architecture with Marginal Preservation for Matrix-Valued Regression
Khang Tran, Hieu Cao, Thinh Pham +3
Regression is essential across many domains but remains challenging in high-dimensional settings, where existing methods often lose spatial structure or demand heavy storage. In th…
MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classification
Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep +7
Whole slide pathology image classification presents challenges due to gigapixel image sizes and limited annotation labels, hindering model generalization. This paper introduces a p…
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.…