Katie Collins

Orcid: 0000-0002-7032-716X

Affiliations:
  • Massachusetts Institute of Technology (MIT), Department of Brain and Cognitive Sciences, Cambridge, MA, USA
  • University of Cambridge, Computational and Biological Learning Lab, UK


According to our database1, Katie Collins authored at least 30 papers between 2020 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience.
CoRR, 2024

Can Large Language Models Understand Symbolic Graphics Programs?
CoRR, 2024

Building Machines that Learn and Think with People.
CoRR, 2024

People use fast, goal-directed simulation to reason about novel games.
CoRR, 2024

Modulating Language Model Experiences through Frictions.
CoRR, 2024

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation.
CoRR, 2024

Large Language Models Must Be Taught to Know What They Don't Know.
CoRR, 2024

Representational Alignment Supports Effective Machine Teaching.
CoRR, 2024

Understanding Subjectivity through the Lens of Motivational Context in Model-Generated Image Satisfaction.
CoRR, 2024

Rich Human Feedback for Text-to-Image Generation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
AI for Mathematics: A Cognitive Science Perspective.
CoRR, 2023

Getting aligned on representational alignment.
CoRR, 2023

The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs.
CoRR, 2023

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time.
CoRR, 2023

Evaluating Language Models for Mathematics through Interactions.
CoRR, 2023

Learning Personalized Decision Support Policies.
CoRR, 2023

On the informativeness of supervision signals.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Human-in-the-Loop Mixup.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Learning to Receive Help: Intervention-Aware Concept Embedding Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GeValDi: Generative Validation of Discriminative Models.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Robotics for the Streets: Open-Source Robotics for Academics.
Proceedings of the IEEE Frontiers in Education Conference, 2023


FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines.
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Human Uncertainty in Concept-Based AI Systems.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
Web-based Elicitation of Human Perception on mixup Data.
CoRR, 2022

Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Eliciting and Learning with Soft Labels from Every Annotator.
Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing, 2022

Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks.
Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021
Learning Signal-Agnostic Manifolds of Neural Fields.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Perceiving unseen objects.
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020


  Loading...