3 papers
cs.CV2026
SegTME-UNI2: A Foundation Model-Based Framework for Generalisable Multiclass Cell Segmentation and LLM-Driven Tumour Microenvironment Characterisation in Histopathology
Wan Siti Halimatul Munirah Wan Ahmad, Faris Syahmi Samidi, Mohammad Badal Ahmmed +3
Characterising the tumour microenvironment (TME) from routine H&E-stained histology images requires simultaneous cell segmentation, feature extraction, and interpretable clinical r…
cs.LG2026
From Flat Facts to Sharp Hallucinations: Detecting Stubborn Errors via Gradient Sensitivity
Yee Zhing Liew, Andrew Huey Ping Tan, Anwar P. P. Abdul Majeed
Traditional hallucination detection fails on "Stubborn Hallucinations" - errors where LLMs are confidently wrong. We propose a geometric solution: Embedding-Perturbed Gradient Sens…
cs.CV2026
GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling
Guojie Li, Tianyi Liu, Anwar P. P. Abdul Majeed +3
Medical image segmentation demands models that achieve high accuracy while maintaining computational efficiency and clinical interpretability. While recent Kolmogorov-Arnold Networ…