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PolyU & OPPO developed DLoRAL, a video super-resolution framework using dual LoRA: CLoRA for temporal consistency and DLoRA for spatial details. Its two-stage training balances quality and speed (10× faster inference), with open-source code/models available. Limited in tiny text recovery but promising for real-time applications.....

On June 29, 2025, the Alibaba International AI Team officially released the new multi-modal large model **Ovis-U1**, marking another major breakthrough in the field of multi-modal artificial intelligence. As the latest masterpiece of the Ovis series, Ovis-U1 integrates multi-modal understanding, image generation, and image editing functions, demonstrating powerful cross-modal processing capabilities, providing new possibilities for developers, researchers, and industry applications. This is a detailed report on Ovis-U1 by AIbase. Ovis-U1

Recently, at Baidu's AI Open Day, Wenxin Kaima, Baidu's intelligent code assistant, achieved a major breakthrough. Its standalone AI-native development environment tool, Comate AI IDE, was officially launched. This industry's first multimodal, multi-agent collaborative AI IDE not only introduces the groundbreaking feature of converting design drafts into code with one click, but also provides efficient, intelligent, and secure programming experiences for domestic enterprises and developers.

This article provides a detailed review of the AI-driven social media management tool SchedPilot, analyzing its core functions such as cross-platform publishing and AI comment assistant, helping creators and marketing teams determine whether this tool is worth using. Understand the differentiated advantages and applicable scenarios of SchedPilot compared to other social media management tools.

In recent years, the field of artificial intelligence has undergone tremendous changes, especially with large language models (LLMs) making remarkable progress in multi-modal tasks. These models have demonstrated strong potential in their ability to understand and generate language, but most current multi-modal models still adopt auto-regressive (AR) architectures, which limit inference processes to be rather monotonous and lacking flexibility. To address this limitation, a research team from The University of Hong Kong and Huawei Noah's Ark Lab has proposed a brand new model – FUDOKI, aiming to break these constraints. The core innovation of FUDOKI is

Tomorrow, the 2025FORCE Original Power Conference will be held in grand style. During the conference, the capability upgrade of the BeanPod Large Model family will be revealed. At the same time, the highly anticipated new BeanPod Video Generation Model will also be officially released. It is reported that this new model has multiple excellent features. In terms of multi-camera narration, through efficient model structure design, as well as multimodal positional encoding and multitask unified modeling technology, the model can seamlessly support unique and stable multi-camera expression, making video narration more smooth and natural.

Recently, the Natural Language Intelligence Team of the Tongyi Lab officially released and open-sourced VRAG-RL — a multi-modal RAG reasoning framework driven by visual perception. It aims to solve the problem of how AI can retrieve key information and conduct fine-grained reasoning from visual languages such as images, tables, design drafts, etc., in real-world business scenarios. Retrieving and reasoning about key information in complex visual document knowledge bases has always been a major challenge in the AI field. Traditional retrieval-augmented generation (RAG) methods struggle when handling visually rich information because they find it difficult to...

Recently, the MiMo-VL multi-modal model developed by Xiaomi Company has taken over the baton from MiMo-7B, showcasing powerful capabilities in multiple fields. The model significantly outperforms the same-size benchmark multi-modal model Qwen2.5-VL-7B in tasks such as general question answering and understanding inference for images, videos, and language, and its performance in GUI Grounding tasks is comparable to that of specialized models, preparing for the arrival of the Agent era.

OpenAI announced significant updates to its image generation API (Responses API), adding new features such as streaming transmission, multi-round editing, and integration with Model Context Protocol (MCP) tools and real-time web data search. These new features not only improve the efficiency of image generation but also provide developers with more flexible creation methods, marking a new stage for AI-driven visual content creation. AIbase has compiled the core highlights of this update and its far-reaching impact on the industry.

Recently, a new evaluation benchmark - RBench-V, specifically designed to test the visual reasoning capabilities of multi-modal large models, was released by research teams from Tsinghua University, Tencent HUNYUAN, Stanford University, and Carnegie Mellon University. The introduction of this benchmark aims to fill the gap in the current evaluation system regarding the model's visual output capabilities, allowing for a more comprehensive understanding of existing model performance. The RBench-V benchmark consists of 803 questions covering multiple fields, including geometry and graph theory, mechanics and electromagnetism, multi-target recognition, and path planning.