Brief

GLM-4, a bilingual Chinese-English model developed by Tsinghua University and Zhipu AI, is highlighted for its strong performance in handling both languages natively. Optimized for agent workflows and featuring a Mixture of Experts architecture, it offers efficient inference and a long context window of up to 128K tokens. This model is particularly beneficial for developers building tools that require seamless integration of Chinese and English content, unlike many English-centric open-source alternatives. AI

Researchers from the Chinese University of Hong Kong, Li Hongsheng's team, have developed MindVLA-U1, a unified architecture for autonomous driving that integrates visual, language, and action (VLA) components. This new model aims to overcome the limitations of previous VLA approaches, which often struggled with planning accuracy and real-time performance, by enabling language understanding to directly influence driving decisions. MindVLA-U1 achieves this through an architecture that processes continuous video streams with memory, uses language-predicted driving intents to guide trajectory generation, and can switch between fast and slow reasoning paths for efficiency and complex scenario handling. AI

A Tsinghua University study suggests that Chinese might offer an advantage over English for instructing AI models in complex engineering tasks. Researchers developed an AI agent capable of optimizing aircraft wing shapes to reduce drag, utilizing a Vision-Language Model to interpret visual data and engineering principles. The AI learned through trial and error, receiving rewards for successful drag reduction, with preliminary findings indicating a slight edge for Chinese language commands. AI

A new benchmark called ESI-Bench has been released by Fei-Fei Li's team to evaluate embodied spatial intelligence in AI. Unlike previous benchmarks that assumed optimal observation, ESI-Bench requires AI agents to actively take actions to gather information, closing the perception-action loop. Initial tests with leading models like GPT-5 and Gemini revealed that current AI struggles with active exploration and decision-making, exhibiting "action blindness" and metacognitive deficits, indicating that the primary challenge lies in strategic action rather than pure perception. AI

A Tsinghua-affiliated robotics company, Stellar Motion Era, has achieved the top position in the RoboChallenge, a global benchmark for embodied AI. Their self-developed embodied model, Era0, demonstrated superior performance across 30 real-world tasks, showcasing advanced capabilities in perception, planning, and control. Era0's success is attributed to a novel approach that deeply integrates Vision-Language-Action (VLA) models with world models, enabling more robust and adaptable physical task execution. AI

Researchers from Tsinghua University's Institute for Intelligent Industry have developed a novel approach using "intermediate representations" to bridge the gap between different data modalities in AI. Their work, presented across four papers at CVPR 2026, introduces a "third language" that allows AI systems to understand and process information more effectively. This method involves creating an intermediary representation, such as Occupancy for robot actions and video generation, or Gaussian Maps for 4D scene reconstruction, which is more easily understood by AI than direct mapping between disparate data types. AI

Tsinghua University in China has awarded a distinguished visiting professor title to German Gref, the CEO of Russia's Sberbank. Gref, who has been sanctioned by the United States, received this honor shortly after signing a partnership agreement with the university for innovative development. The award recognizes his significant contributions to technological transformation and artificial intelligence. AI

Veerabhadran Ramanathan, a recipient of the 2026 Crafoord Prize, is shifting the focus of climate action from 'if' to 'how.' He convened a roundtable of scientists and policymakers to address the urgent need for practical solutions to protect vulnerable populations from accelerating climate extremes over the next 25 years. The discussion highlighted that climate change is a human emergency with unequal impacts, emphasizing the simultaneous necessity of emissions reduction and adaptation strategies for survival. AI

Researchers from Tsinghua University and Tencent ARC Lab have developed Pixal3D, a novel method for generating high-fidelity 3D assets from single images. This technique establishes direct pixel-to-3D correspondences by explicitly lifting pixel features into 3D space, surpassing previous methods that relied on less direct feature injection. The project has released its training code, data preparation toolkit, and inference code, along with a Hugging Face demo for public use. AI