6 papers
When Few Steps Are Enough: Training-Free Acceleration of Identity-Preserved Generation
Dongqi Zheng
Identity-preserved image generation is typically built on many-step diffusion backbones, making personalized generation expensive at deployment time. We show that this cost is ofte…
ALTo: Adaptive-Length Tokenizer for Autoregressive Mask Generation
Lingfeng Wang, Hualing Lin, Senda Chen +5
While humans effortlessly draw visual objects and shapes by adaptively allocating attention based on their complexity, existing multimodal large language models (MLLMs) remain cons…
CAFL-L: Constraint-Aware Federated Learning with Lagrangian Dual Optimization for On-Device Language Models
Dongqi Zheng, Wenjin Fu
We introduce Constraint-Aware Federated Learning with Lagrangian Dual Optimization (CAFL-L), a principled extension of FedAvg that explicitly incorporates device-level resource con…
ARS: Adaptive Reasoning Suppression for Efficient Large Reasoning Language Models
Dongqi Zheng
Large Reasoning Language Models (LRLMs or LRMs) demonstrate remarkable capabilities in complex reasoning tasks, but suffer from significant computational inefficiencies due to over…
A Real-Time On-Device Defect Detection Framework for Laser Power-Meter Sensors via Unsupervised Learning
Dongqi Zheng, Wenjin Fu, Guangzong Chen
We present an automated vision-based system for defect detection and classification of laser power meter sensor coatings. Our approach addresses the critical challenge of identifyi…
Diffusion Models on the Edge: Challenges, Optimizations, and Applications
Dongqi Zheng
Diffusion models have shown remarkable capabilities in generating high-fidelity data across modalities such as images, audio, and video. However, their computational intensity make…