5.1k citations · 9.6k across the 102 of their papers we have counts for
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Multitask Learning Can Improve Worst-Group Outcomes
Atharva Kulkarni, Lucio Dery, Amrith Setlur +3
In order to create machine learning systems that serve a variety of users well, it is vital to not only achieve high average performance but also ensure equitable outcomes across d…
Do LLMs exhibit human-like response biases? A case study in survey design
Lindia Tjuatja, Valerie Chen, Sherry Tongshuang Wu +2
As large language models (LLMs) become more capable, there is growing excitement about the possibility of using LLMs as proxies for humans in real-world tasks where subjective labe…
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
Mikhail Khodak, Edmond Chow, Maria-Florina Balcan +1
Solving a linear system is a fundamental scientific computing primitive for which numerous solvers and preconditioners have been developed. These come with parameters whose…
FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines
Matthew Barker, Emma Kallina, Dhananjay Ashok +6
Even though machine learning (ML) pipelines affect an increasing array of stakeholders, there is little work on how input from stakeholders is recorded and incorporated. We propose…
Where Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms
Nari Johnson, Ángel Alexander Cabrera, Gregory Plumb +1
Machine learning (ML) models that achieve high average accuracy can still underperform on semantically coherent subsets ("slices") of data. This behavior can have significant socie…
Learning Personalized Decision Support Policies
Umang Bhatt, Valerie Chen, Katherine M. Collins +4
Individual human decision-makers may benefit from different forms of support to improve decision outcomes, but when each form of support will yield better outcomes? In this work, w…
Cross-Modal Fine-Tuning: Align then Refine
Junhong Shen, Liam Li, Lucio M. Dery +4
Fine-tuning large-scale pretrained models has led to tremendous progress in well-studied modalities such as vision and NLP. However, similar gains have not been observed in many ot…
Assisting Human Decisions in Document Matching
Joon Sik Kim, Valerie Chen, Danish Pruthi +2
Many practical applications, ranging from paper-reviewer assignment in peer review to job-applicant matching for hiring, require human decision makers to identify relevant matches…
Zeno: An Interactive Framework for Behavioral Evaluation of Machine Learning
Ángel Alexander Cabrera, Erica Fu, Donald Bertucci +4
Machine learning models with high accuracy on test data can still produce systematic failures, such as harmful biases and safety issues, when deployed in the real world. To detect…