Learning to Contextually Aggregate Multi-Source Supervision for Sequence
Labeling

Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling

9 October 2019

Bill Yuchen Lin

Xiang Ren

Papers citing "Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling"

10 / 10 papers shown

Title
WeShap: Weak Supervision Source Evaluation with Shapley Values Naiqing Guan Nick Koudas 65 0 0 16 Jun 2024
Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language Models Fengzhu Zeng Wei Gao 25 5 0 05 Jun 2023
ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak Supervision Anastasiia Sedova Benjamin Roth 28 0 0 14 Apr 2022
A Survey on Programmatic Weak Supervision Jieyu Zhang Cheng-Yu Hsieh Yue Yu Chao Zhang Alexander Ratner 36 91 0 11 Feb 2022
Few-shot Named Entity Recognition with Cloze Questions V. Gatta V. Moscato Marco Postiglione Giancarlo Sperlí 27 4 0 24 Nov 2021
WRENCH: A Comprehensive Benchmark for Weak Supervision Jieyu Zhang Yue Yu Yinghao Li Yujing Wang Yaming Yang Mao Yang Alexander Ratner 27 111 0 23 Sep 2021
Truth Discovery in Sequence Labels from Crowds Nasim Sabetpour Adithya Kulkarni Sihong Xie Qi Li 39 16 0 09 Sep 2021
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data Haoming Jiang Danqing Zhang Tianyu Cao Bing Yin T. Zhao NoLa 30 44 0 16 Jun 2021
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence Tal Schuster Adam Fisch Regina Barzilay 44 228 0 15 Mar 2021
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation Dong-Ho Lee Rahul Khanna Bill Yuchen Lin Jamin Chen Seyeon Lee Qinyuan Ye Elizabeth Boschee Leonardo Neves Xiang Ren 43 22 0 16 Apr 2020