DocLayout-YOLO is a deep learning model designed for document layout analysis, enhancing accuracy and processing speed through diverse synthetic data and global-to-local adaptive perception. The model utilizes the Mesh-candidate BestFit algorithm to generate a large and diverse DocSynth-300K dataset, significantly improving fine-tuning performance across different document types. Additionally, it introduces a globally controllable perception field module to better handle multi-scale variations of document elements. DocLayout-YOLO performs exceptionally well on various downstream datasets, showcasing significant advantages in both speed and accuracy.

AI Co-scientist is a multi-agent AI system developed by Google Research to assist scientific research through artificial intelligence techniques. Built on Gemini 2.0, the system simulates the reasoning process of scientific methods, generating new research hypotheses and experimental plans. Through multi-agent collaboration, utilizing mechanisms such as generation, reflection, ranking, and evolution, it continuously optimizes its output. The main advantages of AI Co-scientist include the efficient generation of novel scientific hypotheses, strong interdisciplinary knowledge integration capabilities, and collaborative capabilities with scientists. Currently in the research phase, the system is being validated for its application potential in fields like biomedicine through partnerships with leading global research institutions.

DocLayout-YOLO is a deep learning model designed for document layout analysis, enhancing accuracy and processing speed through diverse synthetic data and global-to-local adaptive perception. The model utilizes the Mesh-candidate BestFit algorithm to generate a large and diverse DocSynth-300K dataset, significantly improving fine-tuning performance across different document types. Additionally, it introduces a globally controllable perception field module to better handle multi-scale variations of document elements. DocLayout-YOLO performs exceptionally well on various downstream datasets, showcasing significant advantages in both speed and accuracy.

RikiGPT 2.0 is an online platform dedicated to academic research, providing direct access to over 2 million academic resources. It utilizes the latest GPT-4o technology to offer users a deep, comprehensive, and highly detailed writing experience. Users can add their own reference lists to customize their research needs. Furthermore, the platform offers full-text translation services in over 100 languages at no extra cost. RikiGPT 2.0 aims to simplify the academic writing process, enhance research efficiency, and is the ideal tool for academics and students.

The Aria Daily Activities Dataset is a re-release of the first pilot dataset released by the Aria project. This dataset has been updated using new tools and location data to accelerate the development of machine perception and artificial intelligence technologies. The dataset contains first-person video sequences from everyday life scenarios, along with rich sensor data, annotation data, and 3D point cloud data generated by the Aria machine perception service. Researchers can use the specialized tools provided by Aria to quickly start using the dataset for their research.

Starfire Research Assistant, jointly developed by iFlytek and the Institute of Information Resources, Chinese Academy of Sciences, is an AI research assistant. Based on cognitive intelligence large models and massive scientific literature resources, it provides functions such as research achievement investigation, paper reading, and academic writing, significantly improving the efficiency of researchers in literature research and reading, thereby saving their time and energy.

Scholarcy is an online literature summarization tool that can generate summary cards for lengthy articles. It reads through research articles, reports, and book chapters, breaking them down into easily understandable segments in seconds to help users quickly assess the relevance of any literature to their work. It extracts key information such as research participants, data analysis, main findings, and limitations, transforming them into summary cards. Scholarcy can also extract charts and images from literature and create links to open the source references. Users can integrate Scholarcy's browser extension with open-access libraries and build their personal summarization research library through the paid subscription service Scholarcy Library.