collaborators

7 papers

eess.IV2026

SinoDiff: Physics-Consistent Self-Supervised Diffusion for Unified Low-Dose to Standard-Dose PET Sinogram Recovery

Ghulam Nabi Ahmad Hassan Yar, Himashi Peiris, Sharna Jamadar +2

Low-dose positron emission tomography (LD-PET) reduces radiation exposure but leads to poor image quality and hinders diagnostic confidence. Existing supervised LD to standard-dose…

cs.CL2026

Sparse Feature Coactivation Reveals Causal Semantic Modules in Large Language Models

Ruixuan Deng, Xiaoyang Hu, Miles Gilberti +5

We identify semantically coherent, context-consistent network components in large language models (LLMs) using coactivation of sparse autoencoder (SAE) features collected from just…

cs.CV2026

A Generalist Foundation Model for Total-body PET/CT Enables Diagnostic Reporting and System-wide Metabolic Profiling

Wei Chen, Liang Wu, Shuyi Lu +10

Total-body PET/CT enables system-wide molecular imaging, but heterogeneous anatomical and metabolic signals, approximately 2 m axial coverage, and structured radiology semantics ch…

cs.CV2025

Conflict Adaptation in Vision-Language Models

Xiaoyang Hu

A signature of human cognitive control is conflict adaptation: improved performance on a high-conflict trial following another high-conflict trial. This phenomenon offers an accoun…

cs.AR2025

T-MAN: Enabling End-to-End Low-Bit LLM Inference on NPUs via Unified Table Lookup

Jianyu Wei, Qingtao Li, Shijie Cao +5

Large language models (LLMs) are increasingly deployed on customer devices. To support them, current devices are adopting SoCs (System on Chip) with NPUs (Neural Processing Unit) i…

cs.CV2025

On the Suitability of Reinforcement Fine-Tuning to Visual Tasks

Xiaxu Chen, Wei Li, Chunxu Liu +5

Reinforcement Fine-Tuning (RFT) is proved to be greatly valuable for enhancing the reasoning ability of LLMs. Researchers have been starting to apply RFT to MLLMs, hoping it will a…