Tianjin Huang

According to our database, Tianjin Huang authored at least 52 papers between 2016 and 2026.

Collaborative distances:

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

2026

MedFM-Robust: Benchmarking Robustness of Medical Foundation Models.

Xiangxiang Cui, Tianjin Huang, Yifang Wang, Lijie Hu, Lu Yin

CoRR, May, 2026

Margin-Adaptive Confidence Ranking for Reliable LLM Judgement.

Gaojie Jin, Yong Tao, Lijia Yu, Tianjin Huang

CoRR, May, 2026

OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents.

Xinyu Li, Ronghui Mu, Lin Li, Tianjin Huang, Gaojie Jin

CoRR, May, 2026

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation.

Jun Wang, Fengpeng Li, Hang Dong, Tianjin Huang, Wei Han

CoRR, May, 2026

DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation.

Yang Yan, Qiuyan Wang, Tianjin Huang, Qiudong Yu, Kexin Zhang

CoRR, April, 2026

Confusion-Aware Spectral Regularizer for Long-Tailed Recognition.

Ziquan Zhu, Gaojie Jin, Hanruo Zhu, Si-Yuan Lu, Yunxiao Zhang, Zeyu Fu, Ronghui Mu, Guoqiang Zhang, Zhao Sun, Xia Yuhang, Jiaxing Shang, Xiang Li, Lu Liu, Tianjin Huang

CoRR, March, 2026

SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation.

Vishal Thengane, Zhaochong An, Tianjin Huang, Son Lam Phung, Abdesselam Bouzerdoum, Lu Yin, Na Zhao, Xiatian Zhu

CoRR, March, 2026

Dual-Kernel Adapter: Expanding Spatial Horizons for Data-Constrained Medical Image Analysis.

Ziquan Zhu, Hanruo Zhu, Siyuan Lu, Xiang Li, Yanda Meng, Gaojie Jin, Lu Yin, Lijie Hu, Di Wang, Lu Liu, Tianjin Huang

CoRR, February, 2026

Beyond Segmentation: An Oil Spill Change Detection Framework Using Synthetic SAR Imagery.

Chenyang Lai, Shuaiyu Chen, Tianjin Huang, Siyang Song, Guangliang Cheng, Chunbo Luo, Zeyu Fu

CoRR, January, 2026

StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors.

Qinkai Yu, Chong Zhang, Gaojie Jin, Tianjin Huang, Wei Zhou, Wenhui Li, Xiaobo Jin, Bo Huang, Yitian Zhao, Guang Yang, Gregory Yoke Hong Lip, Yalin Zheng, Aline Villavicencio, Yanda Meng

IEEE Trans. Image Process., 2026

Unraveling the impact of environmental factors on wheat yield across the European Union via explainable machine learning.

Wei Zhou, Wang Zhou, Davide Cammarano, Klaus Butterbach-Bahl, Jørgen E. Olesen, Zhixian Lin, Tianjin Huang, Gaochao Cai, Jingwen Zhang, Jianxiu Qiu, Sheng Wang

Comput. Electron. Agric., 2026

SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection.

Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min

Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, 2026

TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting.

Chuanru Ren, Yao Lu, Tianjin Huang, Haowen Zheng, Hengde Zhu, Yunyin Li, Hengxiao Li, Lu Liu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

POT: Inducing Overthinking in LLMs via Black-Box Iterative Optimization.

Xinyu Li, Tianjin Huang, Ronghui Mu, Xiaowei Huang, Gaojie Jin

CoRR, August, 2025

LOST: Low-rank and Sparse Pre-training for Large Language Models.

Jiaxi Li, Lu Yin, Li Shen, Jinjin Xu, Liwu Xu, Tianjin Huang, Wenwu Wang, Shiwei Liu, Xilu Wang

CoRR, August, 2025

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models.

Liangyu Wang, Huanyi Xie, Xinhai Wang, Tianjin Huang, Mengdi Li, Di Wang

CoRR, June, 2025

The Compositional Architecture of Regret in Large Language Models.

Xiangxiang Cui, Shu Yang, Tianjin Huang, Wanyu Lin, Lijie Hu, Di Wang

CoRR, June, 2025

REOBench: Benchmarking Robustness of Earth Observation Foundation Models.

Xiang Li, Yong Tao, Siyuan Zhang, Siwei Liu, Zhitong Xiong, Chunbo Luo, Lu Liu, Mykola Pechenizkiy, Xiao Xiang Zhu, Tianjin Huang

CoRR, May, 2025

Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers.

Gaojie Jin, Tianjin Huang, Ronghui Mu, Xiaowei Huang

CoRR, March, 2025

Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam.

Tianjin Huang, Haotian Hu, Zhenyu Zhang, Gaojie Jin, Xiang Li, Li Shen, Tianlong Chen, Lu Liu, Qingsong Wen, Zhangyang Wang, Shiwei Liu

CoRR, February, 2025

Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning.

Andy Li, Aiden Durrant, Milan Markovic, Tianjin Huang, Souvik Kundu, Tianlong Chen, Lu Yin, Georgios Leontidis

Trans. Mach. Learn. Res., 2025

Few-Shot Oriented Object Detection in Remote Sensing Images via Memorable Contrastive Learning.

Jiawei Zhou, Wuzhou Li, Yi Cao, Hongtao Cai, Tianjin Huang, Gui-Song Xia, Xiang Li

IEEE Trans. Geosci. Remote. Sens., 2025

FS-GNN: Improving Fairness in Graph Neural Networks via Joint Sparsification.

Jiaxu Zhao, Tianjin Huang, Shiwei Liu, Jie Yin, Yulong Pei, Meng Fang, Mykola Pechenizkiy

Neurocomputing, 2025

Traffic congestion predictor: A spatiotemporal graph neural network with congestion-conditional adaptive mechanism and optimization algorithm.

Yutian Liu, Jian Gong, Tianjin Huang, Jinde Cao

Expert Syst. Appl., 2025

LKA: Large Kernel Adapter for Enhanced Medical Image Classification.

Ziquan Zhu, Si-Yuan Lu, Tianjin Huang, Lu Liu, Zhe Liu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning.

Zihang Liu, Tianyu Pang, Oleg Balabanov, Chaoqun Yang, Tianjin Huang, Lu Yin, Yaoqing Yang, Shiwei Liu

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

Composable Interventions for Language Models.

Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Jayant Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Enhancing Robust Fairness via Confusional Spectral Regularization.

Gaojie Jin, Sihao Wu, Jiaxu Liu, Tianjin Huang, Ronghui Mu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training.

Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Benchmarking Audio Deepfake Detection Robustness in Real-World Communication Scenarios.

Haohan Shi, Xiyu Shi, Safak Dogan, Saif Alzubi, Tianjin Huang, Yunxiao Zhang

Proceedings of the 33rd European Signal Processing Conference, 2025

Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective.

Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

RT-GCN: Gaussian-based spatiotemporal graph convolutional network for robust traffic prediction.

Yutian Liu, Soora Rasouli, Melvin Wong, Tao Feng, Tianjin Huang

Inf. Fusion, February, 2024

(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork.

Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen

CoRR, 2024

Are Sparse Neural Networks Better Hard Sample Learners?

Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu

Proceedings of the 35th British Machine Vision Conference, 2024

2023

The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need.

Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu

CoRR, 2023

Enhancing Adversarial Training via Reweighting Optimization Trajectory.

Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner.

Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Are Large Kernels Better Teachers than Transformers for ConvNets?

Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu

Proceedings of the International Conference on Machine Learning, 2023

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!

Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Heterophily-Based Graph Neural Network for Imbalanced Classification.

Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy

Proceedings of the Complex Networks & Their Applications XII, 2023

Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost.

Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Direction-aggregated Attack for Transferable Adversarial Examples.

Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy

ACM J. Emerg. Technol. Comput. Syst., 2022

Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training.

Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu

CoRR, 2022

Superposing many tickets into one: A performance booster for sparse neural network training.

Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks.

Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets.

Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu

Proceedings of the Learning on Graphs Conference, 2022

2021

On Generalization of Graph Autoencoders with Adversarial Training.

Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks.

Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy

Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

calibrated adversarial training.

Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Bridging the Performance Gap between FGSM and PGD Adversarial Training.

Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy

CoRR, 2020

2017

A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat - GLAS Footprints.

Tianjin Huang, Li Jia, Massimo Menenti, Jing Lu, Jie Zhou, Guangcheng Hu

Sensors, 2017

2016

An improved method of using icesat altimetry data to extract Tibetan Plateau glacier thickness change rate.

Tianjin Huang, Li Jia, Jing Lu, Jie Zhou

Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016