Gabe Grand


Top-Down Synthesis for Library Learning. Matthew Bowers, Theo X. Olausson, Lionel Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama. Proceedings of the ACM on Programming Languages, Volume 7, Issue POPL (Jan 2023).
[ACM Digital Library] [arXiv] [GitHub]

“Semantic projection” recovers rich human knowledge of multiple object features from word embeddings. Gabriel Grand, Idan Blank, Francisco Pereira, and Evelina Fedorenko. Nature Human Behaviour (2022).
[Nature] [MIT McGovern Institute] [arXiv]

Identifying concept libraries from language about object structure. Catherine Wong*, William P. McCarthy*, Gabriel Grand*, Yoni Friedman, Joshua B. Tenenbaum, Jacob Andreas, Robert D. Hawkins, and Judith E. Fan. CogSci (2022).
[arXiv] [website] [GitHub]

ChemBERTa-2: Towards Chemical Foundation Models. Walid Ahmad, Elana Simon, Seyone Chithrananda, Gabriel Grand, and Bharath Ramsundar. ELLIS ML for Molecules Worshop (December, 2021).
[paper] [workshop]

ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction. Seyone Chithrananda, Gabriel Grand, and Bharath Ramsundar. NeurIPS ML for Molecules Worshop (December, 2020).

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

On the Flip Side: Identifying Counterexamples in Visual Question Answering. Gabriel Grand, Aron Szanto, Yoon Kim, and Alexander Rush. KDD Deep Learning Day, London, UK (August, 2018).
[arXiv] [KDD]

  View Google Scholar profile

Last updated on January 16, 2023