Zhang, Jiaxin

30 publications

CVPR 2025 COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian Splitting Jiaxin Zhang, Junjun Jiang, Youyu Chen, Kui Jiang, Xianming Liu

AAAI 2025 DocKylin: A Large Multimodal Model for Visual Document Understanding with Efficient Visual Slimming Jiaxin Zhang, Wentao Yang, Songxuan Lai, Zecheng Xie, Lianwen Jin

ICLR 2025 Modality-Specialized Synergizers for Interleaved Vision-Language Generalists Zhiyang Xu, Minqian Liu, Ying Shen, Joy Rimchala, Jiaxin Zhang, Qifan Wang, Yu Cheng, Lifu Huang

NeurIPS 2025 Reframing Gaussian Splatting Densification with Complexity-Density Consistency of Primitives Zhemeng Dong, Junjun Jiang, Youyu Chen, Jiaxin Zhang, Kui Jiang, Xianming Liu

ICLR 2025 UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models Xin Xu, Jiaxin Zhang, Tianhao Chen, Zitong Chao, Jishan Hu, Can Yang

ICML 2025 UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models Xin Xu, Qiyun Xu, Tong Xiao, Tianhao Chen, Yuchen Yan, Jiaxin Zhang, Shizhe Diao, Can Yang, Yang Wang

WACV 2024 DECDM: Document Enhancement Using Cycle-Consistent Diffusion Models Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, Sricharan Kumar

AISTATS 2024 Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods Jiaxin Zhang, Kamalika Das, Sricharan Kumar

CVPR 2024 DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks Jiaxin Zhang, Dezhi Peng, Chongyu Liu, Peirong Zhang, Lianwen Jin

WACV 2024 On the Quantification of Image Reconstruction Uncertainty Without Training Data Jiaxin Zhang, Sirui Bi, Victor Fung

ICMLW 2024 PhaseEvo: Towards Unified Long-Context Prompt Optimization for Large Language Models Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley A. Malin, Sricharan Kumar

ICML 2024 UPOCR: Towards Unified Pixel-Level OCR Interface Dezhi Peng, Zhenhua Yang, Jiaxin Zhang, Chongyu Liu, Yongxin Shi, Kai Ding, Fengjun Guo, Lianwen Jin

NeurIPSW 2023 A Divide-Conquer-Reasoning Approach to Consistency Evaluation and Improvement in Blackbox Large Language Models Wendi Cui, Jiaxin Zhang, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley Malin, Sricharan Kumar

AAAI 2023 Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling Sirui Bi, Victor Fung, Jiaxin Zhang

AAAI 2023 AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution Yu Wang, Ján Drgona, Jiaxin Zhang, Karthik Somayaji Nanjangud Suryanarayana, Malachi Schram, Frank Liu, Peng Li

ICCV 2023 ESTextSpotter: Towards Better Scene Text Spotting with Explicit Synergy in Transformer Mingxin Huang, Jiaxin Zhang, Dezhi Peng, Hao Lu, Can Huang, Yuliang Liu, Xiang Bai, Lianwen Jin

NeurIPS 2023 Interactive Multi-Fidelity Learning for Cost-Effective Adaptation of Language Model with Sparse Human Supervision Jiaxin Zhang, Zhuohang Li, Kamalika Das, Sricharan Kumar

CVPR 2023 M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout Analysis Hiuyi Cheng, Peirong Zhang, Sihang Wu, Jiaxin Zhang, Qiyuan Zhu, Zecheng Xie, Jing Li, Kai Ding, Lianwen Jin

ICLRW 2023 On the Robustness of Diffusion Inversion in Image Manipulation Jiaxin Zhang, Kamalika Das, Sricharan Kumar

CVPR 2022 Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage Zhuohang Li, Jiaxin Zhang, Luyang Liu, Jian Liu

NeurIPS 2022 ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler Jiaxin Zhang, Yashar Moshfeghi

AAAI 2022 Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao

AISTATS 2021 A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models Jiaxin Zhang, Sirui Bi, Guannan Zhang

UAI 2021 Enabling Long-Range Exploration in Minimization of Multimodal Functions Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang

NeurIPS 2021 On the Stochastic Stability of Deep Markov Models Jan Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar

NeurIPSW 2021 Self-Supervised Anomaly Detection via Neural Autoregressive Flows with Active Learning Jiaxin Zhang, Kyle Saleeby, Thomas Feldhausen, Sirui Bi, Alex Plotkowski, David Womble

AAAI 2021 Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution Jiapeng Wang, Chongyu Liu, Lianwen Jin, Guozhi Tang, Jiaxin Zhang, Shuaitao Zhang, Qianying Wang, Yaqiang Wu, Mingxiang Cai

IJCAI 2020 Attention as Relation: Learning Supervised Multi-Head Self-Attention for Relation Extraction Jie Liu, Shaowei Chen, Bingquan Wang, Jiaxin Zhang, Na Li, Tong Xu

NeurIPS 2019 Learning Nonlinear Level Sets for Dimensionality Reduction in Function Approximation Guannan Zhang, Jiaxin Zhang, Jacob Hinkle

AISTATS 2015 Power-Law Graph Cuts Xiangyang Zhou, Jiaxin Zhang, Brian Kulis