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Research - Papers

Explore a selection of our published work on a variety of key research challenges in AI.

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Zero-Shot Activity Recognition with Verb Attribute Induction

Rowan ZellersYejin Choi
2017
EMNLP

In this paper, we investigate large-scale zero-shot activity recognition by modeling the visual and linguistic attributes of action verbs. For example, the verb “salute” has several properties, such… 

Learning a Neural Semantic Parser from User Feedback

Srinivasan IyerIoannis KonstasAlvin Cheungand Luke Zettlemoyer
2017
ACL

We present an approach to rapidly and easily build natural language interfaces to databases for new domains, whose performance improves over time based on user feedback, and requires minimal… 

WebChild 2.0: Fine-Grained Commonsense Knowledge Distillation

Niket TandonGerard de Meloand Gerhard Weikum
2017
ACL

Despite important progress in the area of intelligent systems, most such systems still lack commonsense knowledge that appears crucial for enabling smarter, more human-like decisions. In this paper,… 

Answering Complex Questions Using Open Information Extraction

Tushar KhotAshish Sabharwaland Peter Clark
2017
ACL

While there has been substantial progress in factoid question-answering (QA), answering complex questions remains challenging, typically requiring both a large body of knowledge and inference… 

Semi-supervised sequence tagging with bidirectional language models

Matthew E. PetersWaleed AmmarChandra Bhagavatulaand Russell Power
2017
ACL

Pre-trained word embeddings learned from unlabeled text have become a standard component of neural network architectures for NLP tasks. However, in most cases, the recurrent network that operates… 

Deep Semantic Role Labeling: What Works and What's Next

Luheng HeKenton LeeMike LewisLuke S. Zettlemoyer
2017
ACL

We introduce a new deep learning model for semantic role labeling (SRL) that significantly improves the state of the art, along with detailed analyses to reveal its strengths and limitations. We use… 

Visual Semantic Planning using Deep Successor Representations

Yuke ZhuDaniel GordonEric KolveAli Farhadi
2017
ICCV

A crucial capability of real-world intelligent agents is their ability to plan a sequence of actions to achieve their goals in the visual world. In this work, we address the problem of visual… 

See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content

Roozbeh MottaghiConnor SchenckDieter FoxAli Farhadi
2017
ICCV

Humans have rich understanding of liquid containers and their contents; for example, we can effortlessly pour water from a pitcher to a cup. Doing so requires estimating the volume of the cup,… 

Pros and Cons of Autonomous Weapons Systems

Amitai Etzioni and Oren Etzioni
2017
Military Review

Autonomous weapons systems and military robots are progressing from science fiction movies to designers' drawing boards, to engineering laboratories, and to the battlefield. These machines have… 

Interactive Visualization for Linguistic Structure

Aaron SarnatVidur JoshiCristian Petrescu-Prahovaand Mark Hopkins
2017
EMNLP

We provide a visualization library and web interface for interactively exploring a parse tree or a forest of parses. The library is not tied to any particular linguistic representation, but provides…