Alibaba DAMO Academy, in collaboration with the ModelScope community, recently announced the open sourcing of a new multilingual benchmark testing set, P-MMEval, aimed at comprehensively evaluating the multilingual capabilities of Large Language Models (LLMs) and conducting comparative analysis of cross-language transfer abilities. This testing set covers efficient datasets for both basic and specialized capabilities, ensuring consistency in multilingual coverage across all selected datasets, and provides parallel samples across multiple languages, supporting up to 10 languages from 8 different language families, including English, Chinese, and Arabic.

The Sinan OpenCompass team at the Shanghai Artificial Intelligence Laboratory has collaborated with the Modao ModelScope to launch the Compass Multi-Modal Arena, a new section of a large model evaluation platform focusing on multi-modal large models. Users can upload images and input questions to have two anonymous multi-modal large models generate answers, which can then be subjectively evaluated based on the quality of the generated content, allowing users to select the better-performing model. The platform offers an easy-to-use interface and a unique question bank.

Recently, Alibaba launched an AI data science assistant named DS Assistant, which can automate the entire process from data exploration to model evaluation, making data science work simpler and more efficient.

["Modu Community has released the open source version of GPTS 'ModelScope Agents', allowing users to customize and further develop.", "ModelScope Agents features open source openness, support for various LLM Agents, and finetuning capabilities.", "Users can use ModelScope Agents via Colab links and Notebook links, and install and operate through Python environment."]