Forough Arabshahi

According to our database, Forough Arabshahi authored at least 16 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Route, Interpret, Repeat: Blurring the Line Between Post hoc Explainability and Interpretable Models.

Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich

CoRR, 2023

Augmentation by Counterfactual Explanation -Fixing an Overconfident Classifier.

Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat.

Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich

Proceedings of the International Conference on Machine Learning, 2023

2021

AutoNLU: Detecting, root-causing, and fixing NLU model errors.

Pooja Sethi, Denis Savenkov, Forough Arabshahi, Jack Goetz, Micaela Tolliver, Nicolas Scheffer, Ilknur Kabul, Yue Liu, Ahmed Aly

CoRR, 2021

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules.

Forough Arabshahi, Jennifer Lee, Antoine Bosselut, Yejin Choi, Tom M. Mitchell

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Conversational Neuro-Symbolic Commonsense Reasoning.

Forough Arabshahi, Jennifer Lee, Mikayla Gawarecki, Kathryn Mazaitis, Amos Azaria, Tom M. Mitchell

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Memory Augmented Recursive Neural Networks.

Forough Arabshahi, Zhichu Lu, Sameer Singh, Animashree Anandkumar

CoRR, 2019

Look-up and Adapt: A One-shot Semantic Parser.

Zhichu Lu, Forough Arabshahi, Igor Labutov, Tom M. Mitchell

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Learning Latent Hierarchical Structures via Probabilistic Models and Deep Learning.

Forough Arabshahi

PhD thesis, 2018

Combining Symbolic and Function Evaluation Expressions In Neural Programs.

Forough Arabshahi, Sameer Singh, Animashree Anandkumar

CoRR, 2018

Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs.

Forough Arabshahi, Sameer Singh, Animashree Anandkumar

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Spectral Methods for Correlated Topic Models.

Forough Arabshahi, Anima Anandkumar

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Beyond LDA: A Unified Framework for Learning Latent Normalized Infinitely Divisible Topic Models through Spectral Methods.

Forough Arabshahi, Animashree Anandkumar

CoRR, 2016

2015

Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models].

Forough Arabshahi, Furong Huang, Animashree Anandkumar, Carter T. Butts, Sean M. Fitzhugh

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

2014

Modeling Dynamic Social Interactions via Conditional Latent Tree Models.

Forough Arabshahi, Furong Huang, Animashree Anandkumar, Carter T. Butts

CoRR, 2014

2013

A frequency domain MVDR beamformer for UWB microwave breast cancer imaging in dispersive mediums.

Forough Arabshahi, Sadaf Monajemi, Hamid Sheikhzadeh, Kaamran Raahemifar, Reza Faraji-Dana

Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, 2013