15 papers
FormalAnalyticGeo: A Neural-Symbolic Based Framework for Multimodal Analytic Geometry Problem Generation
Ruoran Xu, Wending Gao, Qiufeng Wang +1
The paper presents FormalAnalyticGeo, a neural‑symbolic framework that automatically generates multimodal analytic geometry problems by converting free‑form text into a formal desc…
Hilbert-Geo: Solving Solid Geometric Problems by Neural-Symbolic Reasoning
Ruoran Xu, Haoyu Cheng, Bin Dong +1
Geometric problem solving, as a typical multimodal reasoning problem, has attracted much attention and made great progress recently, however most of works focus on plane geometry w…
Measuring Model Robustness via Fisher Information: Spectral Bounds, Theoretical Guarantees, and Practical Algorithms
Chong Zhang, Xiang Li, Jia Wang +2
The robustness of deep neural networks is crucial for safety-critical deployments, yet existing evaluation methods are often attack-dependent and lack interpretability. We propose…
Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization
Ruoran Xu, Borong She, Xiaobo Jin +1
Deep learning optimization relies heavily on the assumption of smooth loss landscapes, a condition systematically violated by modern architectures due to non-smooth components such…
Toward Native Multimodal Modeling: A Roadmap
Siyu An, Junru Lu, Junnan Dong +18
Multimodal modeling represents a vital step from modality-agnostic reasoning toward world modeling. While early approaches predominantly rely on late-fusion that assembles encoders…
Divide-and-Conquer Inference for Large-Scale Visual Recognition with Multimodal Large Language Models
Zhipeng Ye, Jiaqi Huang, Feng Jiang +5
Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities across a wide range of vision language tasks. However, when applied to large scale image classificati…