This repository is a curated 'awesome list' of research resources on multimodal learning in medical imaging. It contains no application code, tests, or data pipelines; its sole substantive file is a large README.md that catalogs papers, datasets, benchmarks, and code repositories. Topics span medical vision-language models, report generation, visual question answering, retrieval-augmented generation (RAG), and multimodal LLMs. The list is organized by task and includes links to arXiv PDFs, GitHub code, and dataset sources, with badges indicating publication venues.
This repository is a comprehensive family of GUI automation agents (Mobile-Agent series) developed by Tongyi Lab, Alibaba Group. It provides end-to-end solutions for automating interactions across mobile (Android), desktop (Windows/macOS/Linux), and web platforms using vision-language models. The system perceives GUI elements through screenshots, grounds natural language instructions to actionable commands (click, type, scroll), and executes tasks via platform-specific controllers. The architecture includes multiple agent versions (v1-v3.5, E, UI-S1, PC-Agent) with shared core modules for perception, action parsing, and controller interfaces, alongside training frameworks (VERL) and evaluation suites (Android World, MiniWoB, Mind2Web). Key entry points are version-specific run scripts (e.g., run_ma35.py) and API services for remote agent control. The system relies on external dependencies like ADB for Android, PyAutoGUI for desktop, Playwright for web, and VLMs (Qwen series) for reasoning.