Katherine M. Collins | DeepAI

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∙ 07/28/2023

FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines

Even though machine learning (ML) pipelines affect an increasing array o...

0 Matthew Barker, et al. ∙

∙ 06/25/2023

The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs

Human beings are social creatures. We routinely reason about other agent...

0 Lance Ying, et al. ∙

∙ 06/14/2023

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time

Concept-based models perform prediction using a set of concepts that are...

0 Matthew Barker, et al. ∙

∙ 06/02/2023

Evaluating Language Models for Mathematics through Interactions

The standard methodology of evaluating large language models (LLMs) base...

0 Katherine M. Collins, et al. ∙

∙ 04/13/2023

Learning Personalized Decision Support Policies

Individual human decision-makers may benefit from different forms of sup...

0 Umang Bhatt, et al. ∙

∙ 03/22/2023

Human Uncertainty in Concept-Based AI Systems

Placing a human in the loop may abate the risks of deploying AI systems ...

7 Katherine M. Collins, et al. ∙

∙ 11/02/2022

Web-based Elicitation of Human Perception on mixup Data

Synthetic data is proliferating on the web and powering many advances in...

0 Katherine M. Collins, et al. ∙

∙ 07/02/2022

Eliciting and Learning with Soft Labels from Every Annotator

The labels used to train machine learning (ML) models are of paramount i...

0 Katherine M. Collins, et al. ∙

∙ 05/11/2022

Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks

Human language offers a powerful window into our thoughts – we tell stor...

8 Katherine M. Collins, et al. ∙

∙ 11/11/2021

Learning Signal-Agnostic Manifolds of Neural Fields

Deep neural networks have been used widely to learn the latent structure...

6 Yilun Du, et al. ∙

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