Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: In God We Trust. All Others Must Bring Data. - W. Edwards Deming. Using Word Embeddings to Recognize Idioms
Unsupervised Recognition of Literal and Non-Literal Use of Idiomatic Expressions
CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings
Word Embedding and WordNet Based Metaphor Identification and Interpretation
Dynamic Word Embeddings
Combining Explicit and Implicit Semantic Similarity Information for Word Embeddings
Word Representations via Gaussian Embedding
Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation
Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't
Evaluating Word Embeddings Using a Representative Suite of Practical Tasks
Distilling Word Embeddings: An Encoding Approach
Different Contexts Lead to Different Word Embeddings
Knowledge-Powered Deep Learning for Word Embedding
Learning Sense-specific Word Embeddings By Exploiting Bilingual Resources
A Deeper Look into Dependency-Based Word Embeddings
Latent Semantic Word Sense Induction and Disambiguation
Don't Get Fooled by Word Embeddings-Better Watch their Neighborhood
Computing Linear Discriminants for Idiomatic Sentence Detection
Classifying Idiomatic and Literal Expressions Using Topic Models and Intensity of Emotions
Visual Exploration of Semantic Relationships in Neural Word Embeddings
Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings.
Usability of E-learning tools
Automatically Constructing A Lexicon Of Verb Phrase Idiomatic Combinations
A two-way time of flight ranging scheme for wireless sensor networks
Critical review of the e-loyalty literature: a purchase-centred framework
technical brief : agreement , the f - measure , and reliability in information retrieval .