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End-to-End Weak Supervision

End-to-End Weak Supervision

5 July 2021
Salva Rühling Cachay
Benedikt Boecking
A. Dubrawski
    NoLa
ArXivPDFHTML

Papers citing "End-to-End Weak Supervision"

30 / 30 papers shown
Title
Medifact at PerAnsSumm 2025: Leveraging Lightweight Models for Perspective-Specific Summarization of Clinical Q&A Forums
Medifact at PerAnsSumm 2025: Leveraging Lightweight Models for Perspective-Specific Summarization of Clinical Q&A Forums
Nadia Saeed
34
0
0
15 Mar 2025
Mislabeled examples detection viewed as probing machine learning models:
  concepts, survey and extensive benchmark
Mislabeled examples detection viewed as probing machine learning models: concepts, survey and extensive benchmark
Thomas George
Pierre Nodet
A. Bondu
Vincent Lemaire
VLM
18
0
0
21 Oct 2024
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from
  Multiple Humans
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans
M. Herde
Denis Huseljic
Lukas Rauch
Bernhard Sick
29
1
0
30 Jul 2024
Theoretical Analysis of Weak-to-Strong Generalization
Theoretical Analysis of Weak-to-Strong Generalization
Hunter Lang
David Sontag
Aravindan Vijayaraghavan
21
19
0
25 May 2024
Convergence Behavior of an Adversarial Weak Supervision Method
Convergence Behavior of an Adversarial Weak Supervision Method
Steven An
Sanjoy Dasgupta
13
0
0
25 May 2024
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via
  a Mixup Extension
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension
M. Herde
Lukas Lührs
Denis Huseljic
Bernhard Sick
29
3
0
06 May 2024
Fusing Conditional Submodular GAN and Programmatic Weak Supervision
Fusing Conditional Submodular GAN and Programmatic Weak Supervision
Kumar Shubham
Pranav Sastry
AP Prathosh
19
1
0
16 Dec 2023
Pareto Optimal Learning for Estimating Large Language Model Errors
Pareto Optimal Learning for Estimating Large Language Model Errors
Theodore Zhao
Mu-Hsin Wei
J. S. Preston
Hoifung Poon
14
6
0
28 Jun 2023
Making Binary Classification from Multiple Unlabeled Datasets Almost
  Free of Supervision
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision
Yuhao Wu
Xiaobo Xia
Jun Yu
Bo Han
Gang Niu
Masashi Sugiyama
Tongliang Liu
4
3
0
12 Jun 2023
Transferring Annotator- and Instance-dependent Transition Matrix for
  Learning from Crowds
Transferring Annotator- and Instance-dependent Transition Matrix for Learning from Crowds
Shikun Li
Xiaobo Xia
Jiankang Deng
Shiming Ge
Tongliang Liu
19
15
0
05 Jun 2023
Local Boosting for Weakly-Supervised Learning
Local Boosting for Weakly-Supervised Learning
Rongzhi Zhang
Yue Yu
Jiaming Shen
Xiquan Cui
Chao Zhang
WSOL
34
2
0
05 Jun 2023
Multi-annotator Deep Learning: A Probabilistic Framework for
  Classification
Multi-annotator Deep Learning: A Probabilistic Framework for Classification
M. Herde
Denis Huseljic
Bernhard Sick
19
9
0
05 Apr 2023
Weakly Supervised Label Learning Flows
Weakly Supervised Label Learning Flows
You Lu
Chidubem Arachie
Bert Huang
18
0
0
19 Feb 2023
Analyzing the impact of climate change on critical infrastructure from
  the scientific literature: A weakly supervised NLP approach
Analyzing the impact of climate change on critical infrastructure from the scientific literature: A weakly supervised NLP approach
Tanwi Mallick
Joshua Bergerson
Duane R. Verner
John K Hutchison
L. Levy
Prasanna Balaprakash
25
4
0
03 Feb 2023
WeCheck: Strong Factual Consistency Checker via Weakly Supervised
  Learning
WeCheck: Strong Factual Consistency Checker via Weakly Supervised Learning
Wenhao Wu
Wei Li
Xinyan Xiao
Jiachen Liu
Sujian Li
Yajuan Lv
HILM
18
4
0
20 Dec 2022
Losses over Labels: Weakly Supervised Learning via Direct Loss
  Construction
Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
Dylan Sam
J. Zico Kolter
NoLa
OffRL
24
13
0
13 Dec 2022
Time-Aware Datasets are Adaptive Knowledgebases for the New Normal
Time-Aware Datasets are Adaptive Knowledgebases for the New Normal
Abhijit Suprem
Sanjyot Vaidya
J. Ferreira
C. Pu
21
2
0
22 Nov 2022
Ground Truth Inference for Weakly Supervised Entity Matching
Ground Truth Inference for Weakly Supervised Entity Matching
Renzhi Wu
Alexander Bendeck
Xu Chu
Yeye He
14
8
0
13 Nov 2022
SepLL: Separating Latent Class Labels from Weak Supervision Noise
SepLL: Separating Latent Class Labels from Weak Supervision Noise
Andreas Stephan
Vasiliki Kougia
Benjamin Roth
10
8
0
25 Oct 2022
Adaptive Ranking-based Sample Selection for Weakly Supervised
  Class-imbalanced Text Classification
Adaptive Ranking-based Sample Selection for Weakly Supervised Class-imbalanced Text Classification
Linxin Song
Jieyu Zhang
Tianxiang Yang
M. Goto
15
3
0
06 Oct 2022
Leveraging Instance Features for Label Aggregation in Programmatic Weak
  Supervision
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision
Jieyu Zhang
Linxin Song
Alexander Ratner
56
8
0
06 Oct 2022
XPASC: Measuring Generalization in Weak Supervision by Explainability
  and Association
XPASC: Measuring Generalization in Weak Supervision by Explainability and Association
Luisa März
Ehsaneddin Asgari
Fabienne Braune
Franziska Zimmermann
Benjamin Roth
15
0
0
03 Jun 2022
MiDAS: Multi-integrated Domain Adaptive Supervision for Fake News
  Detection
MiDAS: Multi-integrated Domain Adaptive Supervision for Fake News Detection
Abhijit Suprem
C. Pu
30
7
0
19 May 2022
Evaluating Generalizability of Fine-Tuned Models for Fake News Detection
Evaluating Generalizability of Fine-Tuned Models for Fake News Detection
Abhijit Suprem
C. Pu
21
4
0
15 May 2022
ULF: Unsupervised Labeling Function Correction using Cross-Validation
  for Weak Supervision
ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak Supervision
Anastasiia Sedova
Benjamin Roth
21
0
0
14 Apr 2022
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision
Mayee F. Chen
Daniel Y. Fu
Dyah Adila
Michael Zhang
Frederic Sala
Kayvon Fatahalian
Christopher Ré
19
20
0
24 Mar 2022
Generative Modeling Helps Weak Supervision (and Vice Versa)
Generative Modeling Helps Weak Supervision (and Vice Versa)
Benedikt Boecking
Nicholas Roberts
W. Neiswanger
Stefano Ermon
Frederic Sala
Artur Dubrawski
17
1
0
22 Mar 2022
Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data
  Programming
Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming
Cheng-Yu Hsieh
Jieyu Zhang
Alexander Ratner
18
15
0
02 Mar 2022
A Survey on Programmatic Weak Supervision
A Survey on Programmatic Weak Supervision
Jieyu Zhang
Cheng-Yu Hsieh
Yue Yu
Chao Zhang
Alexander Ratner
19
91
0
11 Feb 2022
Understanding self-supervised Learning Dynamics without Contrastive
  Pairs
Understanding self-supervised Learning Dynamics without Contrastive Pairs
Yuandong Tian
Xinlei Chen
Surya Ganguli
SSL
138
278
0
12 Feb 2021
1