15 citations · 36 across the 6 of their papers we have counts for
6 papers
ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Select
Yuchen Zhuang, Yinghao Li, Jerry Junyang Cheung +5
We study the problem of extracting N-ary relation tuples from scientific articles. This task is challenging because the target knowledge tuples can reside in multiple parts and mod…
SciAnnotate: A Tool for Integrating Weak Labeling Sources for Sequence Labeling
Mengyang Liu, Haozheng Luo, Leonard Thong +3
Weak labeling is a popular weak supervision strategy for Named Entity Recognition (NER) tasks, with the goal of reducing the necessity for hand-crafted annotations. Although there…
Sparse Conditional Hidden Markov Model for Weakly Supervised Named Entity Recognition
Yinghao Li, Le Song, Chao Zhang
Weakly supervised named entity recognition methods train label models to aggregate the token annotations of multiple noisy labeling functions (LFs) without seeing any manually anno…
PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning
Rongzhi Zhang, Yue Yu, Pranav Shetty +2
Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set…
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
Yinghao Li, Pranav Shetty, Lucas Liu +2
We study the problem of learning a named entity recognition (NER) tagger using noisy labels from multiple weak supervision sources. Though cheap to obtain, the labels from weak sup…
Accelerating Primal Solution Findings for Mixed Integer Programs Based on Solution Prediction
Jian-Ya Ding, Chao Zhang, Lei Shen +4
Mixed Integer Programming (MIP) is one of the most widely used modeling techniques for combinatorial optimization problems. In many applications, a similar MIP model is solved on a…