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Found 5 papers, 4 papers with code
TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model
Existing research often focuses on leveraging electronic health records (EHRs) to support clinical trial outcome prediction.
HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding
With a simple training scheme and implementation, HiMAP demonstrates competitive results in terms of success rate and scalability in the field of imitation-learning-only MAPF, showing the potential of imitation-learning-only MAPF equipped with inference techniques.
Unsupervised semantic segmentation of high-resolution UAV imagery for road scene parsing
In this paper, an unsupervised road parsing framework that leverages recent advances in vision language models and fundamental computer vision model is introduced. Initially, a vision language model is employed to efficiently process ultra-large resolution UAV images to quickly detect road regions of interest in the images.
Physics-informed Deep Super-resolution for Spatiotemporal Data
High-fidelity simulation of complex physical systems is exorbitantly expensive and inaccessible across spatiotemporal scales.
TwiBot-22: Towards Graph-Based Twitter Bot Detection
Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse.
