Topological Reconstruction Based on STL Model. - Chen Ping; Zhengyan Zhang; Dingfang Chen; Jiquan Hu; Bin Shan; Li Bo (HCC, 2014)

A fractional-step thermal lattice Boltzmann model for high Peclet number flow. - Lin Deng; Yun Zhang 010; Yanwei Wen; Bin Shan; Huamin Zhou (Comput. Math. Appl., 2015)

Generalized Predictive Control of Temperature on an Atomic Layer Deposition Reactor. - Wenjie He; Hai-Tao Zhang; Zhiyong Chen 001; Bo Chu; Kun Cao 003; Bin Shan; Rong Chen (IEEE Trans. Control. Syst. Technol., 2015)

Unsupervised Bilingual Segmentation using MDL for Machine Translation. - Bin Shan; Hao Wang; Yves Lepage (PACLIC, 2017)

Physics-guided Data Augmentation for Learning the Solution Operator of Linear Differential Equations. - Ye Li; Yiwen Pang; Bin Shan (CCIS, 2022)

ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training. - Bin Shan; Weichong Yin; Yu Sun 004; Hao Tian 005; Hua Wu 003; Haifeng Wang 001 (CoRR, 2022)

ERNIE-UniX2: A Unified Cross-lingual Cross-modal Framework for Understanding and Generation. - Bin Shan; Yaqian Han; Weichong Yin; Shuohuan Wang; Yu Sun 004; Hao Tian 005; Hua Wu 003; Haifeng Wang 001 (CoRR, 2022)

VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations. - Bin Shan; Ye Li; Shengjun Huang (CoRR, 2022)

Multi-cue multi-hypothesis tracking with re-identification for multi-object tracking. - Wen Guo; Yuelong Jin; Bin Shan; Xinmiao Ding; Minghao Wang (Multim. Syst., 2022)

Efficient Discrete Physics-informed Neural Networks for Addressing Evolutionary Partial Differential Equations. - Siqi Chen; Bin Shan; Ye Li (CoRR, 2023)

Multi-view region proposal network predictive learning for tracking. - Wen Guo; Dong Li; Bowen Liang; Bin Shan (Multim. Syst., 2023)

Fault-Tolerant SINS/Doppler Radar/Odometer Integrated Navigation Method Based on Two-Stage Fault Detection Structure. - Bo Yang 039; Feng Liu; Liang Xue; Bin Shan (Entropy, 2023)

Causality-enhanced Discreted Physics-informed Neural Networks for Predicting Evolutionary Equations. - Ye Li; Siqi Chen; Bin Shan; Sheng-Jun Huang (IJCAI, 2024)

MCTBench: Multimodal Cognition towards Text-Rich Visual Scenes Benchmark. - Bin Shan; Xiang Fei; Wei Shi; An-Lan Wang; Guozhi Tang; Lei Liao; Jingqun Tang; Xiang Bai; Can Huang (CoRR, 2024)

ParGo: Bridging Vision-Language with Partial and Global Views. - An-Lan Wang; Bin Shan; Wei Shi; Kun-Yu Lin; Xiang Fei; Guozhi Tang; Lei Liao; Jingqun Tang; Can Huang; Wei-Shi Zheng 001 (AAAI, 2025)

VI-PINNs: Variance-involved physics-informed neural networks for fast and accurate prediction of partial differential equations. - Bin Shan; Ye Li; Sheng-Jun Huang (Neurocomputing, 2025)

OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning. - Ling Fu; Biao Yang; Zhebin Kuang; Jiajun Song; Yuzhe Li; Linghao Zhu; Qidi Luo; Xinyu Wang; Hao Lu 003; Mingxin Huang; Zhang Li; Guozhi Tang; et al. (CoRR, 2025)

Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning. - Jinghui Lu; Haiyang Yu; Siliang Xu; Shiwei Ran; Guozhi Tang; Siqi Wang; Bin Shan; Teng Fu; Hao Feng; Jingqun Tang; Han Wang; Can Huang (CoRR, 2025)

MEML-GRPO: Heterogeneous Multi-Expert Mutual Learning for RLVR Advancement. - Weitao Jia; Jinghui Lu; Haiyang Yu; Siqi Wang; Guozhi Tang; An-Lan Wang; Weijie Yin; Dingkang Yang; Yuxiang Nie; Bin Shan; Hao Feng 009; Irene Li; et al. (CoRR, 2025)