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Task-Oriented Query Reformulation with Reinforcement Learning
Rodrigo Nogueira
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Kyunghyun Cho
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Paper Details:
Month: September
Year: 2017
Location: Copenhagen, Denmark
Venue:
EMNLP |
Citations
URL
Identifying Well-formed Natural Language Questions
Manaal Faruqui
|
Dipanjan Das
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NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval
Canjia Li
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Yingfei Sun
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Ben He
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Le Wang
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Kai Hui
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Andrew Yates
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Le Sun
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Jungang Xu
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Ranking Sentences for Extractive Summarization with Reinforcement Learning
Shashi Narayan
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Shay B. Cohen
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Mirella Lapata
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Johannes Welbl
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Pontus Stenetorp
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Sebastian Riedel
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A Neural Autoencoder Approach for Document Ranking and Query Refinement in Pharmacogenomic Information Retrieval
Jonas Pfeiffer
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Samuel Broscheit
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Rainer Gemulla
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Mathias Göschl
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Joint Modeling for Query Expansion and Information Extraction with Reinforcement Learning
Motoki Taniguchi
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Yasuhide Miura
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Tomoko Ohkuma
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A Reinforcement Learning-driven Translation Model for Search-Oriented Conversational Systems
Wafa Aissa
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Laure Soulier
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Ludovic Denoyer
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https://github.com/nyu-dl/
https://lucene.apache.org/
https://cse.google.com/cse/
https://www.microsoft.com/cognitive-services/en-
Field Of Study
Linguistic Trends
Embeddings
Task
Information Extraction
Question Answering
Language
Chinese
English
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