2021

• Representing partial programs with blended abstract semantics.

  Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum, Armando Solar-Lezama. ICLR 2021.

• Learning to recombine and resample data for compositional generalization.

  Ekin Akyürek, Afra Feyza Akyürek and Jacob Andreas. ICLR 2021.

2020

• Compositional explanations of neurons.

  Jesse Mu and Jacob Andreas. NeurIPS 2020.

• A benchmark for systematic generalization in grounded language understanding.

  Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt and Brenden Lake. NeurIPS 2020.

• Natural language for program search and abstraction learning.

  Cathy Wong, Kevin Ellis, Jacob Andreas and Josh Tenenbaum. AAAI Symposium on Conceptual Abstraction.

• Good-Enough Compositional Data Augmentation.

  Jacob Andreas. ACL 2020.

• Unnatural language processing: bridging the gap between synthetic and natural language data.

  Alana Marzoev, Sam Madden, Frans Kaashoek, Mike Cafarella and Jacob Andreas. NeurIPS workshop on Emergent Communication.

2019

• A survey of reinforcement learning informed by natural language.

  Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson and Tim Rocktäschel. IJCAI 2019.

• Measuring compositionality in representation learning.

  Jacob Andreas. ICLR 2019.