Journal ArticleDOI
Computational generation of referring expressions: A survey
Emiel Krahmer,Kees van Deemter +1 more
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TLDR
The REG problem is introduced and early work in this area is described, discussing what basic assumptions lie behind it, and showing how its remit has widened in recent years.Abstract:
This article offers a survey of computational research on referring expression generation (REG). It introduces the REG problem and describes early work in this area, discussing what basic assumptions lie behind it, and showing how its remit has widened in recent years. We discuss computational frameworks underlying REG, and demonstrate a recent trend that seeks to link REG algorithms with well-established Knowledge Representation techniques. Considerable attention is given to recent efforts at evaluating REG algorithms and the lessons that they allow us to learn. The article concludes with a discussion of the way forward in REG, focusing on references in larger and more realistic settings.read more
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Proceedings ArticleDOI
ReferItGame: Referring to Objects in Photographs of Natural Scenes
TL;DR: A new game to crowd-source natural language referring expressions by designing a two player game that can both collect and verify referring expressions directly within the game and provides an in depth analysis of the resulting dataset.
Proceedings ArticleDOI
Generation and Comprehension of Unambiguous Object Descriptions
TL;DR: The authors proposed a method that can generate an unambiguous description (known as a referring expression) of a specific object or region in an image, and which can also comprehend or interpret such an expression to infer which object is being described.
Journal ArticleDOI
Survey of the state of the art in natural language generation: core tasks, applications and evaluation
Albert Gatt,Emiel Krahmer +1 more
TL;DR: A survey of the state of the art in natural language generation can be found in this article, with an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organized.
Posted Content
Modeling Context in Referring Expressions
TL;DR: This work focuses on incorporating better measures of visual context into referring expression models and finds that visual comparison to other objects within an image helps improve performance significantly.
Proceedings ArticleDOI
GuessWhat?! Visual Object Discovery through Multi-modal Dialogue
TL;DR: This work introduces GuessWhat?
References
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TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
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Artificial Intelligence: A Modern Approach
Stuart Russell,Peter Norvig +1 more
TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.