Data Science for COVID-19 (DS4C)
The DS4C dataset is a structured collection of COVID-19 data from South Korea, based on reports from the Korea Centers for Disease Control & Prevention (KCDC) and local governments. It includes information on infections, patient routes, and various analyses. The dataset has been used for multiple research and visualization projects.
Giới Thiệu Chi Tiết
The Data Science for COVID-19 (DS4C) project provides a comprehensive dataset for analyzing the COVID-19 pandemic in South Korea. The dataset includes detailed information on infections, patient routes, and other relevant data. It has been used for various research and visualization projects, including competitions and academic studies. The data is sourced from the KCDC and local governments, ensuring accuracy and reliability.
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HeartLink - Empathetic Psychological Model
HeartLink is an empathetic psychological model that uses a large language model fine-tuned on a large empathetic Q&A dataset. It can perceive users' emotions and experiences during conversations and provide empathetic responses using rich psychological knowledge, aiming to understand, comfort, and support users. The responses include emoji expressions to bridge the gap with users, offering psychological support and help during consultations.
SoulChat2.0: Psychological Counselor's Digital Twin Framework
SoulChat2.0 is a framework for constructing the digital twin of psychological counselors, designed to support the development of AI applications in mental health. It includes a data generation module and a modeling module, enabling the creation of personalized counseling models based on limited real-world counseling cases.
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.