We have introduced B-score, a new metric designed to detect and quantify biases in large language models (LLMs) by analyzing their response...
We have developed VSRM (Video Super-Resolution Mamba), a robust deep learning framework that advances video super-resolution (VSR) by leveraging...
We have presented complementary advances in decoder design for biomarker segmentation, with two papers accepted in highly regarded venues. One paper...
We have developed a reference-based post-OCR processing pipeline that leverages large language models (LLMs) and ebook references to achieve highly...
We have developed a novel framework for time-efficient and identity-consistent virtual try-on, leveraging an altered variant of diffusion models to advance...
We have developed the Channel-Partitioned Attention Transformer (CPAT), a novel deep learning framework that significantly enhances the performance...
[IoT 2024] Sailing Through Data: Automated Data Acquisition Systems...
We have introduced AISail, a custom embedded hardware and software platform designed to automate data acquisition for machine learning in maritime...
ViExam: Are Vision Language Models Better than Humans...
We have conducted the first comprehensive evaluation of vision-language model (VLM) performance on Vietnamese multimodal educational...
Vision Language Models are Biased
We investigate how memorized knowledge in large language models (LLMs), while useful for many downstream tasks, can also bias vision-language models...
