Fei Tan

According to our database, Fei Tan authored at least 35 papers between 2016 and 2025.

Collaborative distances:

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

2025

Consultant Decoding: Yet Another Synergistic Mechanism.

Chuanghao Ding, Jiaping Wang, Ziqing Yang, Xiaoliang Wang, Dahua Lin, Cam-Tu Nguyen, Fei Tan

CoRR, June, 2025

daDPO: Distribution-Aware DPO for Distilling Conversational Abilities.

Zhengze Zhang, Shiqi Wang, Yiqun Shen, Simin Guo, Dahua Lin, Xiaoliang Wang, Cam-Tu Nguyen, Fei Tan

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Consultant Decoding: Yet Another Synergistic Mechanism.

Chuanghao Ding, Jiaping Wang, Ziqing Yang, Xiaoliang Wang, Dahua Lin, Nguyen Cam-Tu, Fei Tan

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

SynthDoc: Bilingual Documents Synthesis for Visual Document Understanding.

Chuanghao Ding, Xuejing Liu, Wei Tang, Juan Li, Xiaoliang Wang, Rui Zhao, Cam-Tu Nguyen, Fei Tan

CoRR, 2024

Offline RLHF Methods Need More Accurate Supervision Signals.

Shiqi Wang, Zhengze Zhang, Rui Zhao, Fei Tan, Cam-Tu Nguyen

CoRR, 2024

SimCT: A Simple Consistency Test Protocol in LLMs Development Lifecycle.

Fufangchen Zhao, Guoqiang Jin, Rui Zhao, Jiangheng Huang, Fei Tan

CoRR, 2024

What Makes Good Few-shot Examples for Vision-Language Models?

Zhaojun Guo, Jinghui Lu, Xuejing Liu, Rui Zhao, Zhenxing Qian, Fei Tan

CoRR, 2024

Balancing Speciality and Versatility: a Coarse to Fine Framework for Supervised Fine-tuning Large Language Model.

Hengyuan Zhang, Yanru Wu, Dawei Li, Zacc Yang, Rui Zhao, Yong Jiang, Fei Tan

CoRR, 2024

CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models.

Jiawei Gu, Zacc Yang, Chuanghao Ding, Rui Zhao, Fei Tan

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Reward Difference Optimization For Sample Reweighting In Offline RLHF.

Shiqi Wang, Zhengze Zhang, Rui Zhao, Fei Tan, Cam-Tu Nguyen

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

SDA: Simple Discrete Augmentation for Contrastive Sentence Representation Learning.

Dongsheng Zhu, Zhenyu Mao, Jinghui Lu, Rui Zhao, Fei Tan

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Balancing Speciality and Versatility: a Coarse to Fine Framework for Supervised Fine-tuning Large Language Model.

Hengyuan Zhang, Yanru Wu, Dawei Li, Sak Yang, Rui Zhao, Yong Jiang, Fei Tan

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

MGEL: Multigrained Representation Analysis and Ensemble Learning for Text Moderation.

Fei Tan, Changwei Hu, Yifan Hu, Kevin Yen, Zhi Wei, Aasish Pappu, Serim Park, Keqian Li

IEEE Trans. Neural Networks Learn. Syst., October, 2023

What Large Language Models Bring to Text-rich VQA?

Xuejing Liu, Wei Tang, Xinzhe Ni, Jinghui Lu, Rui Zhao, Zechao Li, Fei Tan

CoRR, 2023

What Makes Pre-trained Language Models Better Zero-shot Learners?

Jinghui Lu, Dongsheng Zhu, Weidong Han, Rui Zhao, Brian Mac Namee, Fei Tan

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Deeply Coupled Cross-Modal Prompt Learning.

Xuejing Liu, Wei Tang, Jinghui Lu, Rui Zhao, Zhaojun Guo, Fei Tan

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

CWSeg: An Efficient and General Approach to Chinese Word Segmentation.

Dedong Li, Rui Zhao, Fei Tan

Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, 2023

PUnifiedNER: A Prompting-Based Unified NER System for Diverse Datasets.

Jinghui Lu, Rui Zhao, Brian Mac Namee, Fei Tan

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

2022

What Makes Pre-trained Language Models Better Zero/Few-shot Learners?

Jinghui Lu, Rui Zhao, Brian Mac Namee, Dongsheng Zhu, Weidong Han, Fei Tan

CoRR, 2022

MetaCon: Unified Predictive Segments System with Trillion Concept Meta-Learning.

Keqian Li, Yifan Hu, Logan Palanisamy, Lisa Jones, Akshay Gupta, Jason Grigsby, Ili Selinger, Matt Gillingham, Fei Tan

CoRR, 2022

2021

BERT-Beta: A Proactive Probabilistic Approach to Text Moderation.

Fei Tan, Yifan Hu, Kevin Yen, Changwei Hu

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Hadoop-MTA: a system for Multi Data-center Trillion Concepts Auto-ML atop Hadoop.

Keqian Li, Yifan Hu, Manisha Verma, Fei Tan, Changwei Hu, Tejaswi Kasturi, Kevin Yen

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Elucidation of DNA methylation on N6-adenine with deep learning.

Fei Tan, Tian Tian, Xiurui Hou, Xiang Yu, Lei Gu, Fernanda Mafra, Brian D. Gregory, Zhi Wei, Hakon Hakonarson

Nat. Mach. Intell., 2020

HABERTOR: An Efficient and Effective Deep Hatespeech Detector.

Thanh Tran, Yifan Hu, Changwei Hu, Kevin Yen, Fei Tan, Kyumin Lee, Se Rim Park

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

TNT: Text Normalization based Pre-training of Transformers for Content Moderation.

Fei Tan, Yifan Hu, Changwei Hu, Keqian Li, Kevin Yen

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference.

Bang An, Jie Lyu, Zhenyi Wang, Chunyuan Li, Changwei Hu, Fei Tan, Ruiyi Zhang, Yifan Hu, Changyou Chen

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

DeepVar: An End-to-End Deep Learning Approach for Genomic Variant Recognition in Biomedical Literature.

Chaoran Cheng, Fei Tan, Zhi Wei

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A Deep Learning Approach to Competing Risks Representation in Peer-to-Peer Lending.

Fei Tan, Xiurui Hou, Jie Zhang, Zhi Wei, Zhenyu Yan

IEEE Trans. Neural Networks Learn. Syst., 2019

Modeling and elucidation of housing price.

Fei Tan, Chaoran Cheng, Zhi Wei

Data Min. Knowl. Discov., 2019

Success Prediction on Crowdfunding with Multimodal Deep Learning.

Chaoran Cheng, Fei Tan, Xiurui Hou, Zhi Wei

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

User Response Driven Content Understanding with Causal Inference.

Fei Tan, Zhi Wei, Abhishek Pani, Zhenyu Yan

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

Modeling Item-specific Effects for Video Click.

Fei Tan, Kuang Du, Zhi Wei, Haoran Liu, Chenguang Qin, Ran Zhu

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

A Blended Deep Learning Approach for Predicting User Intended Actions.

Fei Tan, Zhi Wei, Jun He, Xiang Wu, Bo Peng, Haoran Liu, Zhenyu Yan

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Time-Aware Latent Hierarchical Model for Predicting House Prices.

Fei Tan, Chaoran Cheng, Zhi Wei

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016

Modeling Real Estate for School District Identification.

Fei Tan, Chaoran Cheng, Zhi Wei

Proceedings of the IEEE 16th International Conference on Data Mining, 2016