242 citations · 1.5k across the 60 of their papers we have counts for
5 papers · 2 filters
Learning to Recombine and Resample Data for Compositional Generalization
Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas
Flexible neural sequence models outperform grammar- and automaton-based counterparts on a variety of tasks. However, neural models perform poorly in settings requiring compositiona…
Task-Oriented Dialogue as Dataflow Synthesis
Semantic Machines, Jacob Andreas, John Bufe +43
We describe an approach to task-oriented dialogue in which dialogue state is represented as a dataflow graph. A dialogue agent maps each user utterance to a program that extends th…
Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data
Alana Marzoev, Samuel Madden, M. Frans Kaashoek +2
Large, human-annotated datasets are central to the development of natural language processing models. Collecting these datasets can be the most challenging part of the development…
Experience Grounds Language
Yonatan Bisk, Ari Holtzman, Jesse Thomason +9
Language understanding research is held back by a failure to relate language to the physical world it describes and to the social interactions it facilitates. Despite the incredibl…
A Benchmark for Systematic Generalization in Grounded Language Understanding
Laura Ruis, Jacob Andreas, Marco Baroni +2
Humans easily interpret expressions that describe unfamiliar situations composed from familiar parts ("greet the pink brontosaurus by the ferris wheel"). Modern neural networks, by…