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What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties
Alexis Conneau
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German Kruszewski
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Guillaume Lample
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Loïc Barrault
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Marco Baroni
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Paper Details:
Month: July
Year: 2018
Location: Melbourne, Australia
Venue:
ACL |
Citations
URL
Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation
Adam Poliak
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Aparajita Haldar
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Rachel Rudinger
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J. Edward Hu
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Ellie Pavlick
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Aaron Steven White
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Benjamin Van Durme
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Picking Apart Story Salads
Su Wang
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Eric Holgate
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Greg Durrett
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Katrin Erk
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Dissecting Contextual Word Embeddings: Architecture and Representation
Matthew Peters
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Mark Neumann
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Luke Zettlemoyer
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Wen-tau Yih
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Lexicosyntactic Inference in Neural Models
Aaron Steven White
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Rachel Rudinger
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Kyle Rawlins
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Benjamin Van Durme
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InferLite: Simple Universal Sentence Representations from Natural Language Inference Data
Jamie Kiros
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William Chan
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Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov
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James Glass
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An Analysis of Encoder Representations in Transformer-Based Machine Translation
Alessandro Raganato
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Jörg Tiedemann
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Probing sentence embeddings for structure-dependent tense
Geoff Bacon
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Terry Regier
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IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations
Jorge Balazs
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Edison Marrese-Taylor
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Yutaka Matsuo
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https://github.com/facebookresearch/
https://github.com/facebookresearch/
https://openreview.net/group?
https://openreview.net/group?
https://arxiv.org/abs/1612
Field Of Study
Linguistic Trends
Discourse
Lexical Semantics
Embeddings
Syntax
Morphology
Task
Tagging
Sentiment Analysis
Question Answering
Machine Translation
Approach
Representation Learning
Language
English
French
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