Baidu Research has unveiled BGE-VL, a groundbreaking multimodal vector model poised to revolutionize information retrieval. This advanced model promises significant improvements in search accuracy and efficiency.

On March 6th, the Beijing Academy of Artificial Intelligence (BAAI) announced the open-sourcing of its multimodal vector model, BGE-VL. This achievement marks a significant breakthrough in the field of multimodal retrieval. The BGE-VL model achieves state-of-the-art results on various multimodal retrieval tasks, including image-text retrieval and compositional image retrieval, significantly improving the performance of multimodal retrieval.

Alibaba Tongyi Lab has open-sourced ViDoRAG, a novel visual document retrieval and question answering system. ViDoRAG boasts impressive accuracy, achieving a remarkable 79.4% in benchmark tests. This system represents a significant advancement in the field of computer vision and information retrieval.

On February 28th, Baidu Netdisk and Baidu Wenku announced the full launch of DeepSeek-R1 full version. This innovative initiative marks the industry's first achievement of a one-stop "deep thinking + deep delivery" capability.

Regarding rumors of the premature release of the new DeepSeek AI model R2, a Huafu Quant representative responded that all information should be based on official announcements. It is understood that Huafu Quant established DeepSeek AI in July 2023, and successfully launched the DeepSeek-R1 model this past January.

Today, Baidu App announced a major update, officially launching a completely new AI entry, and deeply integrating the Wenxin large model with the capabilities of DeepSeek to provide users with an upgraded experience. The core highlights of this upgrade include the integration of several cutting-edge intelligent features, such as 'AI Search', 'Web Information Refinement', 'Squeeze AI Summary', and 'Digital Human Intelligence'. These features enable the Baidu App to better understand user needs and offer more personalized search results.

In the field of academic research, literature retrieval is a complex and crucial information acquisition task. Researchers need the capability to handle intricate, domain-specific search queries to meet detailed research requirements. However, existing academic search platforms, like Google Scholar, often struggle to address these complex research queries. For example, queries related to non-stationary reinforcement learning using the UCB method require stronger computational and analytical capabilities. Moreover, researchers typically need to spend a significant amount of time and effort manually browsing extensive academic literature when conducting literature reviews.

In multimodal tasks, visual language models (VLMs) play a crucial role, such as in image retrieval, image captioning, and medical diagnosis. These models aim to align visual data with language data for more efficient information processing. However, current VLMs still face significant challenges in understanding negation. Negation is critical in many applications, such as distinguishing between "a room without windows" and "a room with windows." Despite significant progress made by VLMs, existing models fall short when it comes to handling negated statements.

The Alibaba Qwen team recently published a paper titled 'Lessons Learned from the Development of Process Reward Models in Mathematical Reasoning' and introduced two new models in the Qwen2.5-Math-PRM series, featuring 7B and 72B parameters respectively. These models break through the limitations of the existing PRM framework in mathematical reasoning, significantly improving the accuracy and generalization ability of reasoning models through innovative techniques. Mathematical reasoning has long been a major challenge for large language models (LLMs), especially regarding errors in intermediate reasoning steps.

The Encode organization has recently requested court support against OpenAI's plans to transition into a for-profit entity. Encode is a nonprofit organization and a co-sponsor of California's Artificial Intelligence Safety Act. The organization's lawyers stated in a brief that OpenAI's transformation would "undermine" its original mission to develop and deploy artificial intelligence technologies in a safe and beneficial manner for the public. Encode's founder and president, Sneha Revanur, accused Open

Internal communications obtained by TechCrunch reveal that Google is having contractors compare its Gemini AI with Anthropic's Claude, raising questions about compliance. Documents show that contractors responsible for improving Gemini need to evaluate the quality of responses from both Gemini and Claude within a 30-minute timeframe based on criteria like accuracy and detail. Recently, contractors discovered explicit mentions of Claude on Google's internal evaluation platform, including 'I am Cl'

The OpenCompass team from Shanghai Artificial Intelligence Laboratory and ModelScope have jointly launched an upgrade for the large model evaluation platform CompassArena. This upgrade aims to provide users with a more scientific and comprehensive model evaluation experience. Since its launch, the platform has attracted a large number of community users to participate and contribute data. Based on this data, CompassArena continues to optimize, and this upgrade includes the new Judge Copilot feature and improvements to the ranking algorithm.