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09/21/2023
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Large language models (LLMs) have pushed the limits of natural language ...
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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...
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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...
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06/14/2023
Selective Concept Models: Permitting Stakeholder Customisation at Test-Time
Concept-based models perform prediction using a set of concepts that are...
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06/12/2023
Controlling Text-to-Image Diffusion by Orthogonal Finetuning
Large text-to-image diffusion models have impressive capabilities in gen...
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06/02/2023
Evaluating Language Models for Mathematics through Interactions
The standard methodology of evaluating large language models (LLMs) base...
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05/31/2023
Diffused Redundancy in Pre-trained Representations
Representations learned by pre-training a neural network on a large data...
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05/21/2023
Quasi-Monte Carlo Graph Random Features
We present a novel mechanism to improve the accuracy of the recently-int...
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05/12/2023
The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments
Algorithmic risk assessment instruments (RAIs) increasingly inform decis...
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04/13/2023
Learning Personalized Decision Support Policies
Individual human decision-makers may benefit from different forms of sup...
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03/22/2023
Human Uncertainty in Concept-Based AI Systems
Placing a human in the loop may abate the risks of deploying AI systems ...
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03/11/2023
Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap
The neural collapse (NC) phenomenon describes an underlying geometric sy...
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03/11/2023
Robust Learning from Explanations
Machine learning from explanations (MLX) is an approach to learning that...
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02/21/2023
Scalable Infomin Learning
The task of infomin learning aims to learn a representation with high ut...
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02/20/2023
Harms from Increasingly Agentic Algorithmic Systems
Research in Fairness, Accountability, Transparency, and Ethics (FATE) ha...
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02/18/2023
Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents
While humans can extract information from unstructured text with high pr...
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02/03/2023
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers
We propose a new class of linear Transformers called FourierLearner-Tran...
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02/02/2023
Efficient Graph Field Integrators Meet Point Clouds
We present two new classes of algorithms for efficient field integration...
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02/01/2023
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features
The problem of efficient approximation of a linear operator induced by t...
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01/31/2023
Simplex Random Features
We present Simplex Random Features (SimRFs), a new random feature (RF) m...
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01/25/2023
Towards Robust Metrics for Concept Representation Evaluation
Recent work on interpretability has focused on concept-based explanation...
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12/16/2022
Robust Explanation Constraints for Neural Networks
Post-hoc explanation methods are used with the intent of providing insig...
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11/29/2022
Towards More Robust Interpretation via Local Gradient Alignment
Neural network interpretation methods, particularly feature attribution ...
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11/02/2022
Web-based Elicitation of Human Perception on mixup Data
Synthetic data is proliferating on the web and powering many advances in...
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10/31/2022
Iterative Teaching by Data Hallucination
We consider the problem of iterative machine teaching, where a teacher s...
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10/11/2022
Continual Learning by Modeling Intra-Class Variation
It has been observed that neural networks perform poorly when the data o...
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09/25/2022
Can We Automate the Analysis of Online Child Sexual Exploitation Discourse?
Social media's growing popularity raises concerns around children's onli...
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09/19/2022
Concept Embedding Models
Deploying AI-powered systems requires trustworthy models supporting effe...
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07/20/2022
Structural Causal 3D Reconstruction
This paper considers the problem of unsupervised 3D object reconstructio...
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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...
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06/23/2022
Measuring Representational Robustness of Neural Networks Through Shared Invariances
A major challenge in studying robustness in deep learning is defining th...
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05/30/2022
Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study
We present a survey of tools used in the criminal justice system in the ...
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05/30/2022
Chefs' Random Tables: Non-Trigonometric Random Features
We introduce chefs' random tables (CRTs), a new class of non-trigonometr...
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05/18/2022
Multi-disciplinary fairness considerations in machine learning for clinical trials
While interest in the application of machine learning to improve healthc...
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05/13/2022
Perspectives on Incorporating Expert Feedback into Model Updates
Machine learning (ML) practitioners are increasingly tasked with develop...
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05/06/2022
Synthetic Data – what, why and how?
This explainer document aims to provide an overview of the current state...
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05/03/2022
On the Utility of Prediction Sets in Human-AI Teams
Research on human-AI teams usually provides experts with a single label,...
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03/22/2022
Racial Disparities in the Enforcement of Marijuana Violations in the US
Racial disparities in US drug arrest rates have been observed for decade...
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02/24/2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning
The proliferation of computing devices has brought about an opportunity ...
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02/12/2022
Robust Learning from Observation with Model Misspecification
Imitation learning (IL) is a popular paradigm for training policies in r...
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02/02/2022
Approximating Full Conformal Prediction at Scale via Influence Functions
Conformal prediction (CP) is a wrapper around traditional machine learni...
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12/14/2021
Filling gaps in trustworthy development of AI
The range of application of artificial intelligence (AI) is vast, as is ...
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12/05/2021
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates
To interpret uncertainty estimates from differentiable probabilistic mod...
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11/29/2021
Exploring Alignment of Representations with Human Perception
We argue that a valuable perspective on when a model learns good represe...
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11/27/2021
Towards Principled Disentanglement for Domain Generalization
A fundamental challenge for machine learning models is generalizing to o...
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11/25/2021
PolyViT: Co-training Vision Transformers on Images, Videos and Audio
Can we train a single transformer model capable of processing multiple m...
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11/18/2021
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Artificial intelligence (AI) provides a promising substitution for strea...
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10/27/2021
Iterative Teaching by Label Synthesis
In this paper, we consider the problem of iterative machine teaching, wh...
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10/08/2021
Hybrid Random Features
We propose a new class of random feature methods for linearizing softmax...
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09/12/2021