Peilin Yu

CIT 351

115 Waterman St

Providence, RI 02905

I am a Ph.D. Candidate in Computer Science advised by Prof. Stephen Bach.

I primarily work on weak supervision problems where we explore learning with limited, indirect and/or noisy supervisions and minimal human efforts. I also explore how to take advantage of the infinite granuarities from foundation models (GPTs, CLIP etc.) to assist weak supervision systems.

I am a proud 👐🏟🧀 Badger and I got my BS in CS and Math there in 2019.

Email : last_name [at] brown [dot] edu

news

Apr 8, 2022	Website underconstruction 😊

selected publications

AISTATS

Learning from Multiple Noisy Partial Labelers

Yu, Peilin, Ding, Tiffany, and Bach, Stephen H.

In Artificial Intelligence and Statistics (AISTATS) 2022

Bib PDF Code

@inproceedings{yu2022nplm,
  abbr = {AISTATS},
  title = {Learning from Multiple Noisy Partial Labelers},
  author = {Yu, Peilin and Ding, Tiffany and Bach, Stephen H.},
  booktitle = {Artificial Intelligence and Statistics (AISTATS)},
  year = {2022},
  bibtex_show = {true},
  selected = {true},
  pdf = {2106.04530.pdf},
  code = {https://github.com/batsresearch/nplm}
}

Preprint

Learning to Compose Soft Prompts for Compositional Zero-Shot Learning

Yu, Peilin*, Nayak, Nihal V.*, and Bach, Stephen H. (* Co-first Author)

arXiv 2022

PDF Code

ACL

DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction

Zheng, Shun, Han, Xu, Lin, Yankai, Yu, Peilin, Chen, Lu, Huang, Ling, Liu, Zhiyuan, and Xu, Wei

In ACL 2019

Bib PDF Code

@inproceedings{zheng2019diagnre,
  abbr = {ACL},
  title = {DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction},
  author = {Zheng, Shun and Han, Xu and Lin, Yankai and Yu, Peilin and Chen, Lu and Huang, Ling and Liu, Zhiyuan and Xu, Wei},
  booktitle = {ACL},
  year = {2019},
  bibtex_show = {true},
  selected = {true},
  pdf = {1811.02166.pdf},
  code = {https://github.com/thunlp/DIAG-NRE}
}