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Compositional Distributional Models of Meaning
Mehrnoosh Sadrzadeh
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Dimitri Kartsaklis
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Paper Details:
Month: December
Year: 2016
Location: Osaka, Japan
Venue:
COLING |
Citations
URL
A context-based model for Sentiment Analysis in Twitter
Andrea Vanzo
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Danilo Croce
|
Roberto Basili
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Predictability of Distributional Semantics in Derivational Word Formation
Sebastian Padó
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Aurélie Herbelot
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Max Kisselew
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Jan Šnajder
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Machine Translation Evaluation for Arabic using Morphologically-enriched Embeddings
Francisco Guzmán
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Houda Bouamor
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Ramy Baly
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Nizar Habash
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Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings
Paul Felt
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Eric Ringger
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Kevin Seppi
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Implementing a Reverse Dictionary, based on word definitions, using a Node-Graph Architecture
Sushrut Thorat
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Varad Choudhari
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Distributional Inclusion Hypothesis for Tensor-based Composition
Dimitri Kartsaklis
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Mehrnoosh Sadrzadeh
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English-Chinese Knowledge Base Translation with Neural Network
Xiaocheng Feng
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Duyu Tang
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Bing Qin
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Ting Liu
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Compositional Distributional Models of Meaning
Mehrnoosh Sadrzadeh
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Dimitri Kartsaklis
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RuSentiment: An Enriched Sentiment Analysis Dataset for Social Media in Russian
Anna Rogers
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Alexey Romanov
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Anna Rumshisky
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Svitlana Volkova
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Mikhail Gronas
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Alex Gribov
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Learning Semantic Sentence Embeddings using Sequential Pair-wise Discriminator
Badri Narayana Patro
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Vinod Kumar Kurmi
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Sandeep Kumar
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Vinay Namboodiri
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Model-Free Context-Aware Word Composition
Bo An
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Xianpei Han
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Le Sun
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Composition of Word Representations Improves Semantic Role Labelling
Michael Roth
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Kristian Woodsend
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Chinese Poetry Generation with Recurrent Neural Networks
Xingxing Zhang
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Mirella Lapata
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Evaluating Neural Word Representations in Tensor-Based Compositional Settings
Dmitrijs Milajevs
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Dimitri Kartsaklis
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Mehrnoosh Sadrzadeh
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Matthew Purver
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Jointly Learning Word Representations and Composition Functions Using Predicate-Argument Structures
Kazuma Hashimoto
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Pontus Stenetorp
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Makoto Miwa
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Yoshimasa Tsuruoka
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Learning Better Embeddings for Rare Words Using Distributional Representations
Irina Sergienya
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Hinrich Schütze
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Reverse-engineering Language: A Study on the Semantic Compositionality of German Compounds
Corina Dima
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Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents
Pengfei Liu
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Xipeng Qiu
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Xinchi Chen
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Shiyu Wu
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Xuanjing Huang
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A Tableau Prover for Natural Logic and Language
Lasha Abzianidze
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Aspect Level Sentiment Classification with Deep Memory Network
Duyu Tang
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Bing Qin
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Ting Liu
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Charagram: Embedding Words and Sentences via Character n-grams
John Wieting
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Mohit Bansal
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Kevin Gimpel
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Karen Livescu
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Improving Sparse Word Representations with Distributional Inference for Semantic Composition
Thomas Kober
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Julie Weeds
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Jeremy Reffin
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David Weir
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Measuring Thematic Fit with Distributional Feature Overlap
Enrico Santus
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Emmanuele Chersoni
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Alessandro Lenci
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Philippe Blache
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Exploring Vector Spaces for Semantic Relations
Kata Gábor
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Haïfa Zargayouna
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Isabelle Tellier
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Davide Buscaldi
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Thierry Charnois
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Learning Generic Sentence Representations Using Convolutional Neural Networks
Zhe Gan
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Yunchen Pu
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Ricardo Henao
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Chunyuan Li
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Xiaodong He
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Lawrence Carin
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Pointwise HSIC: A Linear-Time Kernelized Co-occurrence Norm for Sparse Linguistic Expressions
Sho Yokoi
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Sosuke Kobayashi
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Kenji Fukumizu
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Jun Suzuki
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Kentaro Inui
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Learning Compositionality Functions on Word Embeddings for Modelling Attribute Meaning in Adjective-Noun Phrases
Matthias Hartung
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Fabian Kaupmann
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Soufian Jebbara
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Philipp Cimiano
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Efficient, Compositional, Order-sensitive n-gram Embeddings
Adam Poliak
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Pushpendre Rastogi
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M. Patrick Martin
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Benjamin Van Durme
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Measuring Semantic Relations between Human Activities
Steven Wilson
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Rada Mihalcea
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Squibs: When the Whole Is Less Than the Sum of Its Parts: How Composition Affects PMI Values in Distributional Semantic Vectors
Denis Paperno
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Marco Baroni
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mwetoolkit+sem: Integrating Word Embeddings in the mwetoolkit for Semantic MWE Processing
Silvio Cordeiro
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Carlos Ramisch
|
Aline Villavicencio
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Cognitively Motivated Distributional Representations of Meaning
Elias Iosif
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Spiros Georgiladakis
|
Alexandros Potamianos
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Word Embedding Approach for Synonym Extraction of Multi-Word Terms
Amir Hazem
|
Béatrice Daille
|
Deep Multilingual Correlation for Improved Word Embeddings
Ang Lu
|
Weiran Wang
|
Mohit Bansal
|
Kevin Gimpel
|
Karen Livescu
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A Word Embedding Approach to Predicting the Compositionality of Multiword Expressions
Bahar Salehi
|
Paul Cook
|
Timothy Baldwin
|
Discriminative Phrase Embedding for Paraphrase Identification
Wenpeng Yin
|
Hinrich Schütze
|
Learning Translation Models from Monolingual Continuous Representations
Kai Zhao
|
Hany Hassan
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Michael Auli
|
Embedding Lexical Features via Low-Rank Tensors
Mo Yu
|
Mark Dredze
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Raman Arora
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Matthew R. Gormley
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Learning Distributed Representations of Sentences from Unlabelled Data
Felix Hill
|
Kyunghyun Cho
|
Anna Korhonen
|
Abstract Meaning Representation for Paraphrase Detection
Fuad Issa
|
Marco Damonte
|
Shay B. Cohen
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Xiaohui Yan
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Yi Chang
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Identifying Semantic Divergences in Parallel Text without Annotations
Yogarshi Vyas
|
Xing Niu
|
Marine Carpuat
|
Olive Oil is Made of Olives, Baby Oil is Made for Babies: Interpreting Noun Compounds Using Paraphrases in a Neural Model
Vered Shwartz
|
Chris Waterson
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Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
Dimitri Kartsaklis
|
Nal Kalchbrenner
|
Mehrnoosh Sadrzadeh
|
An Exploration of Embeddings for Generalized Phrases
Wenpeng Yin
|
Hinrich Schütze
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Pairwise Neural Machine Translation Evaluation
Francisco Guzmán
|
Shafiq Joty
|
Lluís Màrquez
|
Preslav Nakov
|
Cross-Lingual Lexico-Semantic Transfer in Language Learning
Ekaterina Kochmar
|
Ekaterina Shutova
|
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time
Silvio Cordeiro
|
Carlos Ramisch
|
Marco Idiart
|
Aline Villavicencio
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Composing Distributed Representations of Relational Patterns
Sho Takase
|
Naoaki Okazaki
|
Kentaro Inui
|
Learning Monolingual Compositional Representations via Bilingual Supervision
Ahmed Elgohary
|
Marine Carpuat
|
EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks
Muhammad Abdul-Mageed
|
Lyle Ungar
|
Polish evaluation dataset for compositional distributional semantics models
Alina Wróblewska
|
Katarzyna Krasnowska-Kieraś
|
Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings
John Wieting
|
Kevin Gimpel
|
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
Mikhail Khodak
|
Nikunj Saunshi
|
Yingyu Liang
|
Tengyu Ma
|
Brandon Stewart
|
Sanjeev Arora
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Unsupervised Learning of Distributional Relation Vectors
Shoaib Jameel
|
Zied Bouraoui
|
Steven Schockaert
|
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
Dinghan Shen
|
Guoyin Wang
|
Wenlin Wang
|
Martin Renqiang Min
|
Qinliang Su
|
Yizhe Zhang
|
Chunyuan Li
|
Ricardo Henao
|
Lawrence Carin
|
Paraphrase to Explicate: Revealing Implicit Noun-Compound Relations
Vered Shwartz
|
Ido Dagan
|
From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
Peter Young
|
Alice Lai
|
Micah Hodosh
|
Julia Hockenmaier
|
Learning Composition Models for Phrase Embeddings
Mo Yu
|
Mark Dredze
|
evision PDF of 'From Paraphrase Database to Compositional Paraphrase Model and Back
John Wieting
|
Mohit Bansal
|
Kevin Gimpel
|
Karen Livescu
|
Deriving Boolean structures from distributional vectors
German Kruszewski
|
Denis Paperno
|
Marco Baroni
|
Learning to Understand Phrases by Embedding the Dictionary
Felix Hill
|
Kyunghyun Cho
|
Anna Korhonen
|
Yoshua Bengio
|
Phrase Table Induction Using In-Domain Monolingual Data for Domain Adaptation in Statistical Machine Translation
Benjamin Marie
|
Atsushi Fujita
|
MappSent: a Textual Mapping Approach for Question-to-Question Similarity
Amir Hazem
|
Basma El Amel Boussaha
|
Nicolas Hernandez
|
ASAP: Automatic Semantic Alignment for Phrases
Ana Alves
|
Adriana Ferrugento
|
Mariana Lourenço
|
Filipe Rodrigues
|
Dissecting the Practical Lexical Function Model for Compositional Distributional Semantics
Abhijeet Gupta
|
Jason Utt
|
Sebastian Padó
|
Leveraging Preposition Ambiguity to Assess Compositional Distributional Models of Semantics
Samuel Ritter
|
Cotie Long
|
Denis Paperno
|
Marco Baroni
|
Matthew Botvinick
|
Adele Goldberg
|
IDI@NTNU at SemEval-2016 Task 6: Detecting Stance in Tweets Using Shallow Features and GloVe Vectors for Word Representation
Henrik Bøhler
|
Petter Asla
|
Erwin Marsi
|
Rune Sætre
|
NaCTeM at SemEval-2016 Task 1: Inferring sentence-level semantic similarity from an ensemble of complementary lexical and sentence-level features
Piotr Przybyła
|
Nhung T. H. Nguyen
|
Matthew Shardlow
|
Georgios Kontonatsios
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Sophia Ananiadou
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NORMAS at SemEval-2016 Task 1: SEMSIM: A Multi-Feature Approach to Semantic Text Similarity
Kolawole Adebayo
|
Luigi Di Caro
|
Guido Boella
|
The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective
Sabine Schulte im Walde
|
Anna Hätty
|
Stefan Bott
|
You and me... in a vector space: modelling individual speakers with distributional semantics
Aurélie Herbelot
|
Behrang QasemiZadeh
|
Decoding Sentiment from Distributed Representations of Sentences
Edoardo Maria Ponti
|
Ivan Vulić
|
Anna Korhonen
|
Peperomia at SemEval-2018 Task 2: Vector Similarity Based Approach for Emoji Prediction
Jing Chen
|
Dechuan Yang
|
Xilian Li
|
Wei Chen
|
Tengjiao Wang
|
A Systematic Study of Semantic Vector Space Model Parameters
Douwe Kiela
|
Stephen Clark
|
Linguistic Regularities in Sparse and Explicit Word Representations
Omer Levy
|
Yoav Goldberg
|
Fusion of Compositional Network-based and Lexical Function Distributional Semantic Models
Spiros Georgiladakis
|
Elias Iosif
|
Alexandros Potamianos
|
Learning Embeddings for Transitive Verb Disambiguation by Implicit Tensor Factorization
Kazuma Hashimoto
|
Yoshimasa Tsuruoka
|
Fracking Sarcasm using Neural Network
Aniruddha Ghosh
|
Tony Veale
|
Assisting Discussion Forum Users using Deep Recurrent Neural Networks
Jacob Hagstedt P Suorra
|
Olof Mogren
|
A Vector Model for Type-Theoretical Semantics
Konstantin Sokolov
|
Top a Splitter: Using Distributional Semantics for Improving Compound Splitting
Patrick Ziering
|
Stefan Müller
|
Lonneke van der Plas
|
Analysis of Policy Agendas: Lessons Learned from Automatic Topic Classification of Croatian Political Texts
Mladen Karan
|
Jan Šnajder
|
Daniela Širinić
|
Goran Glavaš
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Building a Bagpipe with a Bag and a Pipe: Exploring Conceptual Combination in Vision
Sandro Pezzelle
|
Ravi Shekhar
|
Raffaella Bernardi
|
Distributed Vector Representations for Unsupervised Automatic Short Answer Grading
Oliver Adams
|
Shourya Roy
|
Raghuram Krishnapuram
|
Named Entity Recognition in Swedish Health Records with Character-Based Deep Bidirectional LSTMs
Simon Almgren
|
Sean Pavlov
|
Olof Mogren
|
A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models
Ramy Baly
|
Gilbert Badaro
|
Georges El-Khoury
|
Rawan Moukalled
|
Rita Aoun
|
Hazem Hajj
|
Wassim El-Hajj
|
Nizar Habash
|
Khaled Shaban
|
Compositional Semantics using Feature-Based Models from WordNet
Pablo Gamallo
|
Martín Pereira-Fariña
|
A Graph Based Semi-Supervised Approach for Analysis of Derivational Nouns in Sanskrit
Amrith Krishna
|
Pavankumar Satuluri
|
Harshavardhan Ponnada
|
Muneeb Ahmed
|
Gulab Arora
|
Kaustubh Hiware
|
Pawan Goyal
|
Sense Contextualization in a Dependency-Based Compositional Distributional Model
Pablo Gamallo
|
Gradual Learning of Matrix-Space Models of Language for Sentiment Analysis
Shima Asaadi
|
Sebastian Rudolph
|
“Deep” Learning : Detecting Metaphoricity in Adjective-Noun Pairs
Yuri Bizzoni
|
Stergios Chatzikyriakidis
|
Mehdi Ghanimifard
|
Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders
Tsuneo Kato
|
Atsushi Nagai
|
Naoki Noda
|
Ryosuke Sumitomo
|
Jianming Wu
|
Seiichi Yamamoto
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Learning Phrase Embeddings from Paraphrases with GRUs
Zhihao Zhou
|
Lifu Huang
|
Heng Ji
|
Is Structure Necessary for Modeling Argument Expectations in Distributional Semantics?
Emmanuele Chersoni
|
Enrico Santus
|
Philippe Blache
|
Alessandro Lenci
|
Semantic Composition via Probabilistic Model Theory
Guy Emerson
|
Ann Copestake
|
Learning to Compose Spatial Relations with Grounded Neural Language Models
Mehdi Ghanimifard
|
Simon Dobnik
|
Modeling Derivational Morphology in Ukrainian
Mariia Melymuka
|
Gabriella Lapesa
|
Max Kisselew
|
Sebastian Padó
|
Affordances in Grounded Language Learning
Stephen McGregor
|
KyungTae Lim
|
Do Character-Level Neural Network Language Models Capture Knowledge of Multiword Expression Compositionality?
Ali Hakimi Parizi
|
Paul Cook
|
Learning representations for sentiment classification using Multi-task framework
Hardik Meisheri
|
Harshad Khadilkar
|
Finding The Best Model Among Representative Compositional Models
Masayasu Muraoka
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Sonse Shimaoka
|
Kazeto Yamamoto
|
Yotaro Watanabe
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Naoaki Okazaki
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Kentaro Inui
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No URLs Found
Field Of Study
Linguistic Trends
Discourse
Distributional Semantics
Embeddings
Formal Semantics
Language
English
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