We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
In this paper, we describe a new approach for mining concept associations from large text collections. The concepts are short sequences of words that occur frequently together acr...
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
This paper proposes a novel approach to extract meaningful content information from video by collaborative integration of imageunderstanding and natural language processing. As an...
Natural language processing technology has developed remarkably, but it is still difficult for computers to understand contextual meanings as humans do. The purpose of our work ha...