Stephen H. Bach

Stephen H. Bach

Brown University

H-index: 23

North America-United States

About Stephen H. Bach

Stephen H. Bach, With an exceptional h-index of 23 and a recent h-index of 21 (since 2020), a distinguished researcher at Brown University, specializes in the field of Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Language models in the loop: Incorporating prompting into weak supervision

If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions

Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation

LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons

Leveraging large language models for structure learning in prompted weak supervision

Tasks Algorithmically Given Labels Established via Transferred Symbols (TAGLETS)

Enhancing clip with clip: Exploring pseudolabeling for limited-label prompt tuning

An Adaptive Method for Weak Supervision with Drifting Data

Stephen H. Bach Information

University

Position

Assistant Professor of Computer Science

Citations(all)

6189

Citations(since 2020)

5280

Cited By

2130

hIndex(all)

23

hIndex(since 2020)

21

i10Index(all)

32

i10Index(since 2020)

25

Email

University Profile Page

Brown University

Google Scholar

View Google Scholar Profile

Stephen H. Bach Skills & Research Interests

Machine Learning

Top articles of Stephen H. Bach

Title

Journal

Author(s)

Publication Date

Language models in the loop: Incorporating prompting into weak supervision

ACM/JMS Journal of Data Science

Ryan Smith

Jason A Fries

Braden Hancock

Stephen H Bach

2024/4/8

If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions

arXiv preprint arXiv:2403.16442

Reza Esfandiarpoor

Cristina Menghini

Stephen H Bach

2024/3/25

Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation

arXiv preprint arXiv:2402.18334

Nihal V Nayak

Yiyang Nan

Avi Trost

Stephen H Bach

2024/2/28

LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons

arXiv preprint arXiv:2402.14086

Zheng-Xin Yong

Cristina Menghini

Stephen H Bach

2024/2/21

Leveraging large language models for structure learning in prompted weak supervision

Jinyan Su

Peilin Yu

Jieyu Zhang

Stephen H Bach

2023/12/15

Tasks Algorithmically Given Labels Established via Transferred Symbols (TAGLETS)

Michael Littman

Eli Upfal

Stephen Bach

James Tompkin

2023/9/20

Enhancing clip with clip: Exploring pseudolabeling for limited-label prompt tuning

Advances in Neural Information Processing Systems 36 (NeurIPS 2023)

Cristina Menghini

Andrew Delworth

Stephen H Bach

2023/6/2

An Adaptive Method for Weak Supervision with Drifting Data

arXiv preprint arXiv:2306.01658

Alessio Mazzetto

Reza Esfandiarpoor

Eli Upfal

Stephen H Bach

2023/6/2

Learning to Generate Instructions to Adapt Language Models to New Tasks

Nihal Nayak

Yiyang Nan

Avi Trost

Stephen Bach

2023/11/26

Alfred: A system for prompted weak supervision

arXiv preprint arXiv:2305.18623

Peilin Yu

Stephen Bach

2023/5/29

Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification

arXiv preprint arXiv:2311.07593

Reza Esfandiarpoor

Stephen H Bach

2023/11/10

Low-resource languages jailbreak gpt-4

NeurIPS Socially Responsible Language Modelling Research (SoLaR) 2023

Zheng-Xin Yong

Cristina Menghini

Stephen H Bach

2023/10/3

Learning to compose soft prompts for compositional zero-shot learning

arXiv preprint arXiv:2204.03574

Nihal V Nayak

Peilin Yu

Stephen H Bach

2022/4/7

Tight lower bounds on worst-case guarantees for zero-shot learning with attributes

Advances in Neural Information Processing Systems

Alessio Mazzetto

Cristina Menghini

Andrew Yuan

Eli Upfal

Stephen Bach

2022/12/6

Promptsource: An integrated development environment and repository for natural language prompts

arXiv preprint arXiv:2202.01279

Stephen H Bach

Victor Sanh

Zheng-Xin Yong

Albert Webson

Colin Raffel

...

2022/2/2

Bloom: A 176b-parameter open-access multilingual language model

Teven Le Scao

Angela Fan

Christopher Akiki

Ellie Pavlick

Suzana Ilić

...

2023/11/20

Fairness via explanation quality: Evaluating disparities in the quality of post hoc explanations

Jessica Dai

Sohini Upadhyay

Ulrich Aivodji

Stephen H Bach

Himabindu Lakkaraju

2022/7/26

Learning from multiple noisy partial labelers

Peilin Yu

Tiffany Ding

Stephen H Bach

2022/5/3

Does CLIP bind concepts? Probing compositionality in large image models

arXiv preprint arXiv:2212.10537

Martha Lewis

Nihal V Nayak

Peilin Yu

Qinan Yu

Jack Merullo

...

2022/12/20

TAGLETS: A system for automatic semi-supervised learning with auxiliary data

Proceedings of Machine Learning and Systems

Wasu Piriyakulkij

Cristina Menghini

Ross Briden

Nihal Vivekanand Nayak

Jeffrey Zhu

...

2022/4/22

See List of Professors in Stephen H. Bach University(Brown University)

Co-Authors

H-index: 147
Jure Leskovec

Jure Leskovec

Stanford University

H-index: 139
Larry Davis

Larry Davis

University of Maryland

H-index: 87
Christopher Ré

Christopher Ré

Stanford University

H-index: 73
Lise Getoor

Lise Getoor

University of California, Santa Cruz

H-index: 55
Dianne P O'Leary

Dianne P O'Leary

University of Maryland

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