82 citations · 174 across the 5 of their papers we have counts for
4 papers · 1 filter
Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
Bowen Tan, Yun Zhu, Lijuan Liu +3
Large language models (LLMs) such as T0, FLAN, and OPT-IML, excel in multi-tasking under a unified instruction-following paradigm, where they also exhibit remarkable generalization…
RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs
Bowen Tan, Yun Zhu, Lijuan Liu +5
The recent progress of AI can be largely attributed to large language models (LLMs). However, their escalating memory requirements introduce challenges for machine learning (ML) re…
Learning Data Manipulation for Augmentation and Weighting
Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov +2
Manipulating data, such as weighting data examples or augmenting with new instances, has been increasingly used to improve model training. Previous work has studied various rule- o…
Connecting the Dots Between MLE and RL for Sequence Prediction
Bowen Tan, Zhiting Hu, Zichao Yang +2
Sequence prediction models can be learned from example sequences with a variety of training algorithms. Maximum likelihood learning is simple and efficient, yet can suffer from com…