Youper: Artificial Intelligence For Mental Health Care.
Youper utilizes artificial intelligence to revolutionize mental health care, offering scalable solutions for providers, employers, payers, and life science companies. As the first responder for emotional health issues, Youper provides instant support and integrates seamlessly into existing care workflows.
Detalyadong Panimula
Welcome to Youper, where artificial intelligence meets mental health care. We are dedicated to making mental health care accessible to more people by scaling services and providing instant support through our AI platform. Youper serves as a first responder for individuals in need, enhances care for health professionals, and supports employers in providing better mental health care to their employees. Youper was founded in 2015 by a psychiatrist driven by the goal of democratizing access to treatment. The platform provides behaviour analytics to monitor emotional, psychological, and behavioural health issues. It helps patients manage emotions and behaviours through personalized meditations, enabling users to reformulate thought patterns, think through scenarios, and emotions, and arrive at healthier states of mind.
Higit paAI
DeepSeek-VL2
DeepSeek-VL2 is an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models designed for advanced multimodal understanding. It demonstrates superior capabilities across various tasks, including visual question answering, optical character recognition, document/table/chart understanding, and visual grounding. The model series includes three variants with 1 billion, 2.8 billion, and 4.5 billion activated parameters respectively.
Earkick
Earkick is a free AI-powered chatbot designed to measure and improve mental health in real time, offering personalized support and privacy-focused features.
t4d: Conversion Algorithm from ToMi to T4D Dataset
This project implements the conversion algorithm from the ToMi dataset to the T4D (Thinking is for Doing) dataset, as introduced in the paper https://arxiv.org/abs/2310.03051. It filters examples with Theory of Mind (ToM) questions and adapts the algorithm to account for second-order false beliefs.