no code implementations • EMNLP 2020 • Fei Tan, Yifan Hu, Changwei Hu, Keqian Li, Kevin Yen
In this work, we present a new language pre-training model TNT (Text Normalization based pre-training of Transformers) for content moderation.
1 code implementation • 16 Apr 2024 • Hengyuan Zhang, Yanru Wu, Dawei Li, Zacc Yang, Rui Zhao, Yong Jiang, Fei Tan
In an overall evaluation of both speciality and versatility, CoFiTune consistently outperforms baseline methods across diverse tasks and model scales.
no code implementations • 27 Feb 2024 • Fufangchen Zhao, Guoqiang Jin, Jiaheng Huang, Rui Zhao, Fei Tan
The solution to this problem is often time-consuming and labor-intensive, and there is also an additional cost of secondary deployment, resulting in economic and time losses.
no code implementations • 13 Nov 2023 • Xuejing Liu, Wei Tang, Xinzhe Ni, Jinghui Lu, Rui Zhao, Zechao Li, Fei Tan
This pipeline achieved superior performance compared to the majority of existing Multimodal Large Language Models (MLLM) on four text-rich VQA datasets.
1 code implementation • 29 May 2023 • Xuejing Liu, Wei Tang, Jinghui Lu, Rui Zhao, Zhaojun Guo, Fei Tan
Recent advancements in multimodal foundation models (e. g., CLIP) have excelled in zero-shot generalization.
no code implementations • 21 Dec 2022 • Ke Wang, Mariya Doneva, Jakob Meineke, Thomas Amthor, Ekin Karasan, Fei Tan, Jonathan I. Tamir, Stella X. Yu, Michael Lustig
Here we propose a supervised learning-based method that directly synthesizes contrast-weighted images from the MRF data without going through the quantitative mapping and spin-dynamics simulation.
Generative Adversarial Network Magnetic Resonance Fingerprinting +1
1 code implementation • 27 Nov 2022 • Jinghui Lu, Rui Zhao, Brian Mac Namee, Fei Tan
In this work, we present a ``versatile'' model -- the Prompting-based Unified NER system (PUnifiedNER) -- that works with data from different domains and can recognise up to 37 entity types simultaneously, and theoretically it could be as many as possible.
1 code implementation • 8 Oct 2022 • Dongsheng Zhu, Zhenyu Mao, Jinghui Lu, Rui Zhao, Fei Tan
Contrastive learning has recently achieved compelling performance in unsupervised sentence representation.
1 code implementation • 30 Sep 2022 • Jinghui Lu, Dongsheng Zhu, Weidong Han, Rui Zhao, Brian Mac Namee, Fei Tan
Current methods for prompt learning in zeroshot scenarios widely rely on a development set with sufficient human-annotated data to select the best-performing prompt template a posteriori.
no code implementations • 9 Mar 2022 • Keqian Li, Yifan Hu, Logan Palanisamy, Lisa Jones, Akshay Gupta, Jason Grigsby, Ili Selinger, Matt Gillingham, Fei Tan
Accurate understanding of users in terms of predicative segments play an essential role in the day to day operation of modern internet enterprises.
no code implementations • EMNLP 2021 • Fei Tan, Yifan Hu, Kevin Yen, Changwei Hu
Text moderation for user generated content, which helps to promote healthy interaction among users, has been widely studied and many machine learning models have been proposed.
no code implementations • EMNLP 2020 • Thanh Tran, Yifan Hu, Changwei Hu, Kevin Yen, Fei Tan, Kyumin Lee, Serim Park
HABERTOR inherits BERT's architecture, but is different in four aspects: (i) it generates its own vocabularies and is pre-trained from the scratch using the largest scale hatespeech dataset; (ii) it consists of Quaternion-based factorized components, resulting in a much smaller number of parameters, faster training and inferencing, as well as less memory usage; (iii) it uses our proposed multi-source ensemble heads with a pooling layer for separate input sources, to further enhance its effectiveness; and (iv) it uses a regularized adversarial training with our proposed fine-grained and adaptive noise magnitude to enhance its robustness.
no code implementations • EMNLP 2020 • Bang An, Jie Lyu, Zhenyi Wang, Chunyuan Li, Changwei Hu, Fei Tan, Ruiyi Zhang, Yifan Hu, Changyou Chen
The neural attention mechanism plays an important role in many natural language processing applications.
no code implementations • 5 Jun 2020 • Chaoran Cheng, Fei Tan, Zhi Wei
We consider the problem of Named Entity Recognition (NER) on biomedical scientific literature, and more specifically the genomic variants recognition in this work.
no code implementations • 11 Oct 2018 • Fei Tan, Zhi Wei, Jun He, Xiang Wu, Bo Peng, Haoran Liu, Zhenyu Yan
In this work, we focus on pre- dicting attrition, which is one of typical user intended actions.