14 citations · 31 across the 22 of their papers we have counts for
7 papers · 1 filter
Migratable AI: Personalizing Dialog Conversations with migration context
Ravi Tejwani, Boris Katz, Cynthia Breazeal
The migration of conversational AI agents across different embodiments in order to maintain the continuity of the task has been recently explored to further improve user experience…
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…
Investigating the Decoders of Maximum Likelihood Sequence Models: A Look-ahead Approach
Yu-Siang Wang, Yen-Ling Kuo, Boris Katz
We demonstrate how we can practically incorporate multi-step future information into a decoder of maximum likelihood sequence models. We propose a "k-step look-ahead" module to con…
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…