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07/26/2023
Evaluating the Moral Beliefs Encoded in LLMs
This paper presents a case study on the design, administration, post-pro...
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05/31/2023
An Invariant Learning Characterization of Controlled Text Generation
Controlled generation refers to the problem of creating text that contai...
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10/25/2022
Useful Confidence Measures: Beyond the Max Score
An important component in deploying machine learning (ML) in safety-crit...
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07/28/2022
Measuring Causal Effects of Data Statistics on Language Model's `Factual' Predictions
Large amounts of training data are one of the major reasons for the high...
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06/01/2022
In the Eye of the Beholder: Robust Prediction with Causal User Modeling
Accurately predicting the relevance of items to users is crucial to the ...
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05/27/2022
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior
The increasing size and complexity of modern ML systems has improved the...
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02/24/2022
DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation
Natural language processing (NLP) algorithms have become very successful...
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09/02/2021
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond
A fundamental goal of scientific research is to learn about causal relat...
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06/08/2021
Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
Deep learning algorithms have shown promising results in visual question...
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02/20/2021
On Calibration and Out-of-domain Generalization
Out-of-domain (OOD) generalization is a significant challenge for machin...
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01/18/2021
Model Compression for Domain Adaptation through Causal Effect Estimation
Recent improvements in the predictive quality of natural language proces...
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05/27/2020
CausaLM: Causal Model Explanation Through Counterfactual Language Models
Understanding predictions made by deep neural networks is notoriously di...
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10/24/2019