Zihan Dong

According to our database, Zihan Dong authored at least 19 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

LUCID-SAE: Learning Unified Vision-Language Sparse Codes for Interpretable Concept Discovery.

Difei Gu, Yunhe Gao, Gerasimos Chatzoudis, Zihan Dong, Guoning Zhang, Bangwei Guo, Yang Zhou, Mu Zhou, Dimitris N. Metaxas

CoRR, February, 2026

Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals.

Zihan Dong, Zhixian Zhang, Yang Zhou, Can Jin, Ruijia Wu, Linjun Zhang

CoRR, February, 2026

Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training.

Ran Xu, Tianci Liu, Zihan Dong, Tony Yu, Ilgee Hong, Carl Yang, Linjun Zhang, Tao Zhao, Haoyu Wang

CoRR, February, 2026

ManuRAG: Multi-modal Retrieval Augmented Generation for Manufacturing Question Answering (Early Version).

Yunqing Li, Zihan Dong, Farhad Ameri, Jianbang Zhang

CoRR, January, 2026

Labels or Preferences? Budget-Constrained Learning with Human Judgments over AI-Generated Outputs.

Zihan Dong, Ruijia Wu, Linjun Zhang

CoRR, January, 2026

2025

AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play.

Ran Xu, Yuchen Zhuang, Zihan Dong, Jonathan Wang, Yue Yu, Joyce C. Ho, Linjun Zhang, Haoyu Wang, Wenqi Shi, Carl Yang

CoRR, September, 2025

Avoid Catastrophic Forgetting with Rank-1 Fisher from Diffusion Models.

Zekun Wang, Anant Gupta, Zihan Dong, Christopher J. MacLellan

CoRR, September, 2025

Towards General Computer Control with Hierarchical Agents and Multi-Level Action Spaces.

Zihan Dong, Xinyu Fan, Zixiang Tang, Yunqing Li

CoRR, September, 2025

Contrastive Network Representation Learning.

Zihan Dong, Xin Zhou, Ryumei Nakada, Lexin Li, Linjun Zhang

CoRR, September, 2025

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing.

Tianci Liu, Zihan Dong, Linjun Zhang, Haoyu Wang, Jing Gao

CoRR, February, 2025

A non-negative garrote shrinkage network with adaptive Swish for rotating machinery fault diagnosis under noisy environment.

Pengcheng Zhong, Zhenyu Liu, Rui Li, Hui Liu, Xiaoqi Yang, Zihan Dong, Jianrong Tan

Eng. Appl. Artif. Intell., 2025

Multiscale calibration networks with pseudo label for bearing fault diagnosis under class-imbalanced data and multi-rate sampling scenarios.

Zhenyu Liu, Zihan Dong, Hui Liu, Pengcheng Zhong, Weiqiang Jia, Jianrong Tan

Adv. Eng. Informatics, 2025

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing.

Tianci Liu, Ruirui Li, Zihan Dong, Hui Liu, Xianfeng Tang, Qingyu Yin, Linjun Zhang, Haoyu Wang, Jing Gao

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Experimental Demonstration of $47 \times 800 \text{Gbps}$ Classical Communication and QKD Coexistence Over 101.6 Km HCF.

Tianqi Dou, Weiwen Kong, Lei Zhang, Song Gao, Lipeng Feng, Zhenhua Li, Yuheng Xie, Wenpeng Gao, Peizhe Han, Peng Li, Zihan Dong, Nan Lu, Jianjun Tang

Proceedings of the European Conference on Optical Communications, 2025

2024

LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information.

Zihan Dong, Wei Jiang, Hongyu Li, Andrew T. Dewan, Hongyu Zhao

Briefings Bioinform., July, 2024

Visible-hidden hybrid automatic feature engineering via multi-agent reinforcement learning.

Zhenyu Liu, Donghao Zhang, Hui Liu, Zihan Dong, Weiqiang Jia, Jianrong Tan

Knowl. Based Syst., 2024

FNSPID: A Comprehensive Financial News Dataset in Time Series.

Zihan Dong, Xinyu Fan, Zhiyuan Peng

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Students' Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming.

Zhengdong Zhang, Zihan Dong, Yang Shi, Thomas W. Price, Noboru Matsuda, Dongkuan Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Enhancing Bloodstain Analysis Through AI-Based Segmentation: Leveraging Segment Anything Model for Crime Scene Investigation.

Zihan Dong, Zhengdong Zhang

CoRR, 2023