The general theme that these papers follow is symbolic reasoning and grounding to structured meaning representations and program induction.
Here’s the list. Happy reading!
Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering Ramakrishna Vedantam, Karan Desai, Stefan Lee, Marcus Rohrbach, Dhruv Batra, Devi Parikh
Neural Programmer-Interpreters Scott Reed, Nando de Freitas
Program-Guided Image Manipulators Jiayuan Mao, Xiuming Zhang, Yikai Li, William T Freeman, Joshua B Tenenbaum, Jiajun Wu
Learning Compositional Neural Programs with Recursive Tree Search and Planning Thomas Pierrot, Guillaume Ligner, Scott Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas
Neural module networks Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein
Neural Compositional Denotational Semantics for Question Answering Nitish Gupta, Mike Lewis
Learning programs: A hierarchical Bayesian approach Percy Liang, Michael I Jordan, Dan Klein
Synthesizing program input grammars Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang