2.3k citations · 6.5k across the 77 of their papers we have counts for
6 papers · 1 filter
Arc-swift: A Novel Transition System for Dependency Parsing
Peng Qi, Christopher D. Manning
Transition-based dependency parsers often need sequences of local shift and reduce operations to produce certain attachments. Correct individual decisions hence require global info…
Key-Value Retrieval Networks for Task-Oriented Dialogue
Mihail Eric, Christopher D. Manning
Neural task-oriented dialogue systems often struggle to smoothly interface with a knowledge base. In this work, we seek to address this problem by proposing a new neural dialogue a…
Get To The Point: Summarization with Pointer-Generator Networks
Abigail See, Peter J. Liu, Christopher D. Manning
Neural sequence-to-sequence models have provided a viable new approach for abstractive text summarization (meaning they are not restricted to simply selecting and rearranging passa…
Naturalizing a Programming Language via Interactive Learning
Sida I. Wang, Samuel Ginn, Percy Liang +1
Our goal is to create a convenient natural language interface for performing well-specified but complex actions such as analyzing data, manipulating text, and querying databases. H…
SceneSeer: 3D Scene Design with Natural Language
Angel X. Chang, Mihail Eric, Manolis Savva +1
Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark…
A Copy-Augmented Sequence-to-Sequence Architecture Gives Good Performance on Task-Oriented Dialogue
Mihail Eric, Christopher D. Manning
Task-oriented dialogue focuses on conversational agents that participate in user-initiated dialogues on domain-specific topics. In contrast to chatbots, which simply seek to sustai…