Model Detail
Crow-4B-Opus-4.6-Distill-Heretic_Qwen3.5
—ALPINE: Closed-Loop Adaptive Privacy Budget Allocation for Mobile Edge Crowdsensing
arXiv:2510.17162v2 Announce Type: replace Abstract: Mobile edge crowdsensing (MECS) enables large-scale real-time sensing services, but its continuous data collection and transmission pipeline exposes terminal devices to dynamic privacy risks. Existing privacy protection schemes in MECS typically re
From Synthetic Data to Real Restorations: Diffusion Model for Patient-specific Dental Crown Completion
arXiv:2603.26588v2 Announce Type: replace-cross Abstract: We present ToothCraft, a diffusion-based model for the contextual generation of tooth crowns, trained on artificially created incomplete teeth. Building upon recent advancements in conditioned diffusion models for 3D shapes, we developed a mo
STDDN: A Physics-Guided Deep Learning Framework for Crowd Simulation
arXiv:2604.02756v1 Announce Type: new Abstract: Accurate crowd simulation is crucial for public safety management, emergency evacuation planning, and intelligent transportation systems. However, existing methods, which typically model crowds as a collection of independent individual trajectories, ar
IndoorCrowd: A Multi-Scene Dataset for Human Detection, Segmentation, and Tracking with an Automated Annotation Pipeline
arXiv:2604.02032v1 Announce Type: cross Abstract: Understanding human behaviour in crowded indoor environments is central to surveillance, smart buildings, and human-robot interaction, yet existing datasets rarely capture real-world indoor complexity at scale. We introduce IndoorCrowd, a multi-scene