Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
Natural language understanding systems require a knowledge base provided with conceptual representations reflecting the structure of human beings' cognitive system. Although ...
Models of language learning play a central role in a wide range of applications: from psycholinguistic theories of how people acquire new word knowledge, to information systems th...
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...