VisualTrans: A Benchmark for Real-World Visual Transformation Reasoning

Yuheng Ji^*, Yipu Wang^*, Yuyang Liu, Xiaoshuai Hao, Yue Liu, Yuting Zhao, Huaihai Lyu, Xiaolong Zheng (^*Equal contribution)

• VisualTrans is the first real-world benchmark for Visual Transformation Reasoning (VTR), evaluating spatial, procedural and quantitative reasoning across 12 human-object interaction tasks. While current models perform well on static tasks, they show significant limitations in dynamic, multi-step reasoning, revealing critical gaps in temporal and causal understanding for intelligent systems.

OpenCUA: Open Foundations for Computer-Use Agents

Xinyuan Wang^*, Bowen Wang^*, Dunjie Lu^*, Junlin Yang^*, Tianbao Xie^*, Junli Wang^*, et al., Yipu Wang, Heng Wang, Diyi Yang, Victor Zhong, Y.Charles, Zhilin Yang, Tao Yu

• We present OpenCUA, a comprehensive open-source framework for scaling CUA data and foundation models which includes an annotation infrastructure, the first large-scale computer-use task dataset and a scalable pipeline that transforms demonstrations into state–action pairs with reflective long Chain-of-Thought reasoning. Our end-to-end agent model, OpenCUA-32B achieves an average success rate of 32.5% on OSWorld-Verified, establishing a new state-of-the-art (SOTA) among open-source models and surpassing OpenAI CUA (GPT-4o).

Wavelet attention-powered neural network framework with hierarchical dynamic frequency learning for lithium-ion battery state of health prediction

Yipu Wang, Huan Wang

• We propose WAPHF, a wavelet attention-powered hierarchical dynamic frequency learning framework for lithium battery SOH prediction. By integrating CNN with wavelet transform and dynamic frequency-focused attention, our method effectively addresses frequency aliasing issues and outperforms state-of-the-art approaches across three datasets.