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Chao-Ning Zhang

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Preprint Sep 2026

MoR-MLLM: Mixture of Recursions for Efficient Multimodal Large Language Models

Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across vision and language tasks. However, their massive computational and memory demands hinder real-world deployment. While recent efforts reduce costs by employing lightweight language backbones, existing paradigms remain co...

Peng-Cheng Zheng, Chao-Ning Zhang, Jia-Xing Yan et al. · 0 citations
#machine learning Preprint Jul 2026

Hypernetwork-Parameterized Spatially Adaptive Neural Operators for PDE Learning

A spatially adaptive neural operator (SANO), which replaces this spatially shared parameterization with a spatially continuous field of location-dependent operator parameters, which consistently outperforms competitive neural-operator, hypernetwork-based, and physics-informed baselines.

Jia-Quan Zhang, Chao-Ning Zhang, Shu-Xu Chen et al. · 0 citations
#artificial intelligence Preprint Aug 2026

When and What to Teach: Budget-Aware Online Adaptation for Web Agents

A budget-aware framework that systematically orchestrates when and what to teach and integrates a solvability-aware teacher gate to dictate the teacher model and a score-guided turn selection mechanism to decide what informative turns to retain is proposed.

Jian-Wei Zhang, Si-Han Cao, Peng-Cheng Zheng et al. · 0 citations
Preprint Jul 2026

Geometry-aware Incremental Neural Operator for Long-Horizon PDE prediction

A geometry-aware incremental neural operator (GeoIncNO) for stable long-horizon PDE prediction and a mean--fluctuation decoupled reconstruction mechanism, where stable mean structures and dynamic fluctuations are fused separately, and phase correction is applied only to the zero-mean fluctuation component.

Jia-Quan Zhang, Shuxu Chen, Haifan Meng et al. · 0 citations
Conference Open access Sep 2026

Salient-Residual Decoupled Multi-View Learning for Clustering

This paper proposes salient-residual decoupled multi-view learning for clustering, SRDMVC, introducing a novel decomposition-fusion iterative optimization, which separates the feature space into a salient space and a residual subspace effectively and fuses them using a novel attention mechanism.

Gao-Kai Wang, Yazhou Ren, Feng-Yu Zhang et al. · 0 citations
Jul 2026

HERO: History-Enriched Rollout Training for Long-Horizon Autoregressive Neural Operators

Experiments show that HERO consistently improves long-horizon accuracy, stable rollout length, and out-of-distribution robustness at no inference-time cost, indicating that history-enriched relative supervision is effective for stabilizing long-horizon autoregressive prediction.

Jia-Quan Zhang, Shuxu Chen, Haifan Meng et al. · 0 citations

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