Tianxin Wei

According to our database, Tianxin Wei authored at least 22 papers between 2020 and 2024.

Collaborative distances:

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

2024

LLM-Forest for Health Tabular Data Imputation.

Xinrui He, Yikun Ban, Jiaru Zou, Tianxin Wei, Curtiss B. Cook, Jingrui He

CoRR, 2024

Unleashing the Power of LLMs as Multi-Modal Encoders for Text and Graph-Structured Data.

Jiacheng Lin, Kun Qian, Haoyu Han, Nurendra Choudhary, Tianxin Wei, Zhongruo Wang, Sahika Genc, Edward W. Huang, Sheng Wang, Karthik Subbian, Danai Koutra, Jimeng Sun

CoRR, 2024

WAPITI: A Watermark for Finetuned Open-Source LLMs.

Lingjie Chen, Ruizhong Qiu, Siyu Yuan, Zhining Liu, Tianxin Wei, Hyunsik Yoo, Zhichen Zeng, Deqing Yang, Hanghang Tong

CoRR, 2024

Scalable and Effective Generative Information Retrieval.

Hansi Zeng, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, Hamed Zamani

Proceedings of the ACM on Web Conference 2024, 2024

Meta Clustering of Neural Bandits.

Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He

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

Graph Mixup on Approximate Gromov-Wasserstein Geodesics.

Zhichen Zeng, Ruizhong Qiu, Zhe Xu, Zhining Liu, Yuchen Yan, Tianxin Wei, Lei Ying, Jingrui He, Hanghang Tong

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language Models as Semantic Indexers.

Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond.

Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation.

Zhuang Zhuang, Tianxin Wei, Lingbo Liu, Heng Qi, Yanming Shen, Baocai Yin

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

2023

Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs.

Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang

IEEE Data Eng. Bull., 2023

Meta-Learning with Neural Bandit Scheduler.

Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He

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

Adaptive Test-Time Personalization for Federated Learning.

Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He

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

NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning.

Tianxin Wei, Zeming Guo, Yifan Chen, Jingrui He

Proceedings of the International Conference on Machine Learning, 2023

Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning.

Xinrui He, Tianxin Wei, Jingrui He

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Neural Collaborative Filtering Bandits via Meta Learning.

Yikun Ban, Yunzhe Qi, Tianxin Wei, Jingrui He

CoRR, 2022

Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.

Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Comprehensive Fair Meta-learned Recommender System.

Tianxin Wei, Jingrui He

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Causal Intervention for Leveraging Popularity Bias in Recommendation.

Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling, Yongdong Zhang

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.

Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Unpaired Multimodal Neural Machine Translation via Reinforcement Learning.

Yijun Wang, Tianxin Wei, Qi Liu, Enhong Chen

Proceedings of the Database Systems for Advanced Applications, 2021

2020

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.

Tianxin Wei, Fuli Feng, Jiawei Chen, Chufeng Shi, Ziwei Wu, Jinfeng Yi, Xiangnan He

CoRR, 2020

Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning.

Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, Wei Wang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020