NLP Highlights
Ein Podcast von Allen Institute for Artificial Intelligence
145 Folgen
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24 - Improving Hypernymy Detection with an Integrated Path-based and Distributional Method
Vom: 27.6.2017 -
23 - Get To The Point: Summarization with Pointer-Generator Networks
Vom: 26.6.2017 -
22 - Deep Multitask Learning for Semantic Dependency Parsing, with Noah Smith
Vom: 16.6.2017 -
21 - Contextual Explanation Networks, with Maruan Al-Shedivat
Vom: 15.6.2017 -
20 - A simple neural network module for relational reasoning
Vom: 14.6.2017 -
19 - End-to-end Differentiable Proving, with Tim Rocktäschel
Vom: 12.6.2017 -
18 - Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema
Vom: 9.6.2017 -
17 - pix2code: Generating Code from a Graphical User Interface Screenshot
Vom: 8.6.2017 -
16 - Arc-swift: A Novel Transition System for Dependency Parsing
Vom: 7.6.2017 -
15 - Attention and Augmented Recurrent Neural Networks
Vom: 6.6.2017 -
14 - Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning
Vom: 5.6.2017 -
13 - Question Answering from Unstructured Text by Retrieval and Comprehension
Vom: 2.6.2017 -
12 - Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
Vom: 1.6.2017 -
11 - Relation Extraction with Matrix Factorization and Universal Schemas
Vom: 29.5.2017 -
10 - A Syntactic Neural Model for General-Purpose Code Generation
Vom: 26.5.2017 -
09 - Learning to Generate Reviews and Discovering Sentiment
Vom: 25.5.2017 -
08 - Finding News Citations for Wikipedia
Vom: 24.5.2017 -
07 - Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks
Vom: 23.5.2017 -
06 - Design Challenges for Entity Linking
Vom: 22.5.2017 -
05 - Transition-Based Dependency Parsing with Stack Long Short-Term Memory
Vom: 19.5.2017
**The podcast is currently on hiatus. For more active NLP content, check out the Holistic Intelligence Podcast linked below.** Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.