AGI-Eval Review Community

AGI-Eval Review Community is a joint venture between renowned universities and organizations such as Shanghai Jiao Tong University, Tongji University, East China Normal University, and DataWhale.Large Model ReviewCommunity.

Community Mission and Vision

With the mission of "Evaluate and help AI become a better partner for human beings", AGI-Eval is committed to building a fair, credible, scientific and comprehensive evaluation ecosystem. The community focuses on evaluating the general ability of basic models in human cognition and problem solving tasks, aiming to directly correlate and measure the fit between the models and human decision-making and cognitive abilities through a series of well-designed evaluation tasks, thus revealing the applicability and effectiveness of AI models in real life.

Evaluation System and Criteria

1. Diversified Assessment Methods: The AGI-Eval evaluation community combines several public evaluation schemes and builds its own set of large language model evaluation schemes covering multiple evaluation modalities and massive privatized datasets. These evaluation methods include, but are not limited to, question and answer, text generation, reading comprehension, logical reasoning, etc., in order to comprehensively evaluate the various abilities of AI models.
2. Authoritative Rankings and Dynamic Updates: Based on a unified evaluation standard, the AGI-Eval evaluation community provides comprehensive proficiency score rankings for the industry's major language models. These rankings are transparent and authoritative, helping users gain insight into the strengths and weaknesses of each model. At the same time, the list is regularly updated to ensure that users can keep up with the cutting edge of technology and easily find the model solution that best meets their needs.

Review Sets and Data Sets

1. Public Academic Review Collection: The AGI-Eval review community aggregates industry open resources for users to download and use freely. These resources cover a wide range of fields and dimensions, providing rich data support for the evaluation.
2. Official Build Your Own Review Collection: In addition to public academic review sets, the AGI-Eval review community has also built its own review sets covering multi-domain and multi-dimensional model reviews. These review sets are carefully designed and optimized to more accurately assess the capabilities of AI models.
3. User-Built Review Sets: The community supports users to upload their personal review sets to build an open source community. This initiative not only enriches the resources of review sets, but also promotes communication and cooperation among users.

Community Functions and Features

1. man-machine competition: Collaborating with the big model through the form of interesting questions and answers, users can experience cutting-edge technology and participate in the definition of industry benchmarks. This feature not only enhances the user's sense of participation, but also helps to improve the user's understanding and cognition of AI technology.
2. Private dataset hosting service for college bulls: The community provides a private dataset hosting service for university bulls to meet higher level review needs. This service provides a convenient data storage and sharing platform for research organizations and scholars.
3. Highly active user platform: The community has a large number of crowdsourced users to ensure the continuous recovery of high-quality real data. These users cover a wide range of fields and dimensions, providing rich data resources and diverse evaluation scenarios for evaluation.
4. Strict vetting mechanism: The community has implemented a dual review mechanism of machine review and human review to ensure worry-free data quality. This mechanism effectively guarantees the accuracy and reliability of the assessment results.

Application Scenarios and Value

1. NLP Algorithm Development: Developers can use the AGI-Eval evaluation community to test and optimize text generation models, significantly improving the quality and effectiveness of generated text. This feature helps to promote technological progress and innovation in the field of natural language processing.
2. Research Laboratory Assistant: Scholars can utilize the AGI-Eval evaluation community as a powerful tool to assess the performance of new methods, accelerate the research process in the field of natural language processing, and promote academic innovation.
3. Enterprise applications and quality control: Commercial companies can utilize the AGI-Eval review community for quality control of their own chatbots, automated content generation and other products. This feature helps to improve the quality and user experience of products and enhance market competitiveness.