15 citations · 61 across the 31 of their papers we have counts for
5 papers · 1 filter
Learning a natural-language to LTL executable semantic parser for grounded robotics
Christopher Wang, Candace Ross, Yen-Ling Kuo +2
Children acquire their native language with apparent ease by observing how language is used in context and attempting to use it themselves. They do so without laborious annotations…
Compositional Networks Enable Systematic Generalization for Grounded Language Understanding
Yen-Ling Kuo, Boris Katz, Andrei Barbu
Humans are remarkably flexible when understanding new sentences that include combinations of concepts they have never encountered before. Recent work has shown that while deep netw…
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas
Yen-Ling Kuo, Boris Katz, Andrei Barbu
We demonstrate a reinforcement learning agent which uses a compositional recurrent neural network that takes as input an LTL formula and determines satisfying actions. The input LT…
Deep compositional robotic planners that follow natural language commands
Yen-Ling Kuo, Boris Katz, Andrei Barbu
We demonstrate how a sampling-based robotic planner can be augmented to learn to understand a sequence of natural language commands in a continuous configuration space to move and…
Measuring Social Biases in Grounded Vision and Language Embeddings
Candace Ross, Boris Katz, Andrei Barbu
We generalize the notion of social biases from language embeddings to grounded vision and language embeddings. Biases are present in grounded embeddings, and indeed seem to be equa…