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In the Eye of the Beholder: Robust Prediction with Causal User Modeling



Amir Feder , Guy Horowitz , Yoav Wald , Roi Reichart , Nir Rosenfeld


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CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior



Eldar David Abraham , Karel D'Oosterlinck , Amir Feder , Yair Ori Gat , Atticus Geiger , Christopher Potts , Roi Reichart , Zhengxuan Wu


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DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation



Nitay Calderon , Eyal Ben-David , Amir Feder , Roi Reichart

* Our code and data are available at https://github.com/nitaytech/DoCoGen 

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Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond



Amir Feder , Katherine A. Keith , Emaad Manzoor , Reid Pryzant , Dhanya Sridhar , Zach Wood-Doughty , Jacob Eisenstein , Justin Grimmer , Roi Reichart , Margaret E. Roberts , Brandon M. Stewart , Victor Veitch , Diyi Yang


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Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions



Daniel Rosenberg , Itai Gat , Amir Feder , Roi Reichart

* ACL 2021. Our code and data are available at https://danrosenberg.github.io/rad-measure/ 

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On Calibration and Out-of-domain Generalization



Yoav Wald , Amir Feder , Daniel Greenfeld , Uri Shalit

* 24 pages, 6 figures 

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Model Compression for Domain Adaptation through Causal Effect Estimation



Guy Rotman , Amir Feder , Roi Reichart

* Under review 

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CausaLM: Causal Model Explanation Through Counterfactual Language Models



Amir Feder , Nadav Oved , Uri Shalit , Roi Reichart

* Our code and data are available at: https://amirfeder.github.io/CausaLM/ Under review for the Computational Linguistics journal 

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