Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects. Gabriel Grand and Yonatan Belinkov. Proceedings of the 2nd Workshop on Shortcomings in Vision and Language (SiVL) at NAACL-HLT, Minneapolis, MN (June, 2019).
[arXiv] [ACL] Best Paper Award, SiVL Workshop, NAACL 2019
Learning Interpretable and Bias-Free Models for Visual Question Answering. Gabriel Grand. Harvard Undergraduate Thesis, advised by Alexander Rush and presented to the Department of Computer Science (2018).
[PDF] Hoopes Prize
Semantic Projection: Recovering Human Knowledge of Multiple, Distinct Object Features from Word Embeddings Gabriel Grand, Idan Blank, Francisco Pereira, and Evelina Fedorenko. 32nd CUNY Conference on Human Sentence Processing, Boulder, CO (March, 2019).