Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings. - Gabriel Grand; Idan Asher Blank; Francisco Pereira 001; Evelina Fedorenko (CoRR, 2018)

On the Flip Side: Identifying Counterexamples in Visual Question Answering. - Gabriel Grand; Aron Szanto (CoRR, 2018)

Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects. - Gabriel Grand; Yonatan Belinkov (CoRR, 2019)

ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction. - Seyone Chithrananda; Gabriel Grand; Bharath Ramsundar (CoRR, 2020)

Identifying concept libraries from language about object structure. - Catherine Wong; William P. McCarthy; Gabriel Grand; Yoni Friedman; Josh Tenenbaum 001; Jacob Andreas; Robert D. Hawkins; Judith E. Fan (CogSci, 2022)

ChemBERTa-2: Towards Chemical Foundation Models. - Walid Ahmad; Elana Simon; Seyone Chithrananda; Gabriel Grand; Bharath Ramsundar (CoRR, 2022)

Top-Down Synthesis for Library Learning. - Matthew Bowers; Theo X. Olausson; Catherine Wong; Gabriel Grand; Joshua B. Tenenbaum; Kevin Ellis; Armando Solar-Lezama (CoRR, 2022)

Evaluating statistical language models as pragmatic reasoners. - Benjamin Lipkin; Lionel Wong; Gabriel Grand; Josh Tenenbaum 001 (CogSci, 2023)

Grounded physical language understanding with probabilistic programs and simulated worlds. - Cedegao Zhang; Lionel Wong; Gabriel Grand; Josh Tenenbaum 001 (CogSci, 2023)

Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs. - Alexander K. Lew; Tan Zhi-Xuan; Gabriel Grand; Vikash K. Mansinghka (CoRR, 2023)

From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought. - Lionel Wong; Gabriel Grand; Alexander K. Lew; Noah D. Goodman; Vikash K. Mansinghka; Jacob Andreas; Joshua B. Tenenbaum (CoRR, 2023)

Top-Down Synthesis for Library Learning. - Matthew Bowers; Theo X. Olausson; Lionel Wong; Gabriel Grand; Joshua B. Tenenbaum; Kevin Ellis; Armando Solar-Lezama (Proc. ACM Program. Lang., 2023)

LILO: Learning Interpretable Libraries by Compressing and Documenting Code. - Gabriel Grand; Lionel Wong; Matthew Bowers; Theo X. Olausson; Muxin Liu; Joshua B. Tenenbaum; Jacob Andreas (ICLR, 2024)

Loose LIPS Sink Ships: Asking Questions in Battleship with Language-Informed Program Sampling. - Gabriel Grand; Valerio Pepe; Jacob Andreas; Joshua B. Tenenbaum (CoRR, 2024)

Stream of Search (SoS): Learning to Search in Language. - Kanishk Gandhi; Denise Lee; Gabriel Grand; Muxin Liu; Winson Cheng; Archit Sharma; Noah D. Goodman (CoRR, 2024)

Elements of World Knowledge (EWOK): A cognition-inspired framework for evaluating basic world knowledge in language models. - Anna A. Ivanova; Aalok Sathe; Benjamin Lipkin; Unnathi Kumar; Setayesh Radkani; Thomas Hikaru Clark; Carina Kauf; Jennifer Hu 001; R. T. Pramod; Gabriel Grand; Vivian C. Paulun; Maria Ryskina; et al. (CoRR, 2024)

Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo. - João Loula; Benjamin LeBrun; Li Du; Ben Lipkin; Clemente Pasti; Gabriel Grand; Tianyu Liu 004; Yahya Emara; Marjorie Freedman; Jason Eisner; Ryan Cotterell; Vikash Mansinghka 001; et al. (ICLR, 2025)

Self-Steering Language Models. - Gabriel Grand; Joshua B. Tenenbaum; Vikash K. Mansinghka; Alexander K. Lew; Jacob Andreas (CoRR, 2025)