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MedCAGD: Context-Aware Gated Decoder for Efficient Medical Image Segmentation
Saad Wazir, Patrick Dominique Vibild, Dinh Phu Tran +2
Medical image segmentation relies on the ability of encoder-decoder architectures to translate rich feature representations into accurate pixel-level predictions under challenging…
FreqOrtho-SR: Frequency-Guided Orthogonal Expert Learning for Real-World Image Super-Resolution
Minh Son Hoang, Dinh Phu Tran, Quyen Nguyen Duc +2
Diffusion prior-based methods have shown impressive results in real-world image super-resolution (ISR), yet two key challenges persist: balancing pixel-level fidelity with semantic…
TB-AVA: Text as a Semantic Bridge for Audio-Visual Parameter Efficient Finetuning
Seongah Kim, Dinh Phu Tran, Hyeontaek Hwang +3
Audio-visual understanding requires effective alignment between heterogeneous modalities, yet cross-modal correspondence remains challenging when temporally aligned audio and visua…
SAT: Selective Aggregation Transformer for Image Super-Resolution
Dinh Phu Tran, Thao Do, Saad Wazir +3
Transformer-based approaches have revolutionized image super-resolution by modeling long-range dependencies. However, the quadratic computational complexity of vanilla self-attenti…
EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering
Thao Do, Dinh Phu Tran, An Vo +2
Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts increase latency, memory use, a…
Knowing When to Answer: Adaptive Confidence Refinement for Reliable Audio-Visual Question Answering
Dinh Phu Tran, Jihoon Jeong, Saad Wazir +4
We present a formal problem formulation for \textit{Reliable} Audio-Visual Question Answering (-AVQA), where we prefer abstention over answering incorrectly. While rec…