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03/22/2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Artificial intelligence (AI) researchers have been developing and refini...
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03/16/2023
ART: Automatic multi-step reasoning and tool-use for large language models
Large language models (LLMs) can perform complex reasoning in few- and z...
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12/06/2022
Adaptive Testing of Computer Vision Models
Vision models often fail systematically on groups of data that share com...
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11/07/2022
Fixing Model Bugs with Natural Language Patches
Current approaches for fixing systematic problems in NLP models (e.g. re...
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02/28/2021
Model-Agnostic Explainability for Visual Search
What makes two images similar? We propose new approaches to generate mod...
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11/21/2020
Explaining by Removing: A Unified Framework for Model Explanation
Researchers have proposed a wide variety of model explanation approaches...
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11/06/2020
Feature Removal Is a Unifying Principle for Model Explanation Methods
Researchers have proposed a wide variety of model explanation approaches...
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10/27/2020
Shapley Flow: A Graph-based Approach to Interpreting Model Predictions
Many existing approaches for estimating feature importance are problemat...
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06/29/2020
True to the Model or True to the Data?
A variety of recent papers discuss the application of Shapley values, a ...
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04/01/2020
Understanding Global Feature Contributions Through Additive Importance Measures
Understanding the inner workings of complex machine learning models is a...
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02/12/2020
Deep Transfer Learning for Physiological Signals
Deep learning is increasingly common in healthcare, yet transfer learnin...
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11/27/2019
Explaining Models by Propagating Shapley Values of Local Components
In healthcare, making the best possible predictions with complex models ...
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06/25/2019
Learning Explainable Models Using Attribution Priors
Two important topics in deep learning both involve incorporating humans ...
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01/23/2018
Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data
Time series data constitutes a distinct and growing problem in machine l...
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01/23/2018
Hybrid Gradient Boosting Trees and NeuralNetworks for Forecasting Operating Room Data
Time series data constitutes a distinct and growing problem in machine l...
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05/22/2017
A Unified Approach to Interpreting Model Predictions
Understanding why a model makes a certain prediction can be as crucial a...
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11/22/2016