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Word Embeddings

Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to vectors of real numbers.

Techniques for learning word embeddings can include Word2Vec, GloVe, and other neural network-based approaches that train on an NLP task such as language modeling or document classification.

( Image credit: Dynamic Word Embedding for Evolving Semantic Discovery )

Papers

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Showing 2426–2450 of 4002 papers

TitleStatusHype
Hypothesis Testing based Intrinsic Evaluation of Word Embeddings—0
I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification—0
ICL-HD at SemEval-2016 Task 10: Improving the Detection of Minimal Semantic Units and their Meanings with an Ontology and Word Embeddings—0
Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings—0
Identification of Indigenous Knowledge Concepts through Semantic Networks, Spelling Tools and Word Embeddings—0
Identifying Aggression and Toxicity in Comments using Capsule Network—0
Identifying and interpreting non-aligned human conceptual representations using language modeling—0
Identifying and Mitigating Gender Bias in Hyperbolic Word Embeddings—0
Identifying attack and support argumentative relations using deep learning—0
Identifying Cognates in English-Dutch and French-Dutch by means of Orthographic Information and Cross-lingual Word Embeddings—0
Identifying Reference Spans: Topic Modeling and Word Embeddings help IR—0
Identity-sensitive Word Embedding through Heterogeneous Networks—0
Igbo Diacritic Restoration using Embedding Models—0
Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes—0
IITK at the FinSim Task: Hypernym Detection in Financial Domain via Context-Free and Contextualized Word Embeddings—0
IITP at EmoInt-2017: Measuring Intensity of Emotions using Sentence Embeddings and Optimized Features—0
IITPB at SemEval-2017 Task 5: Sentiment Prediction in Financial Text—0
Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search—0
Image Captioning using Deep Stacked LSTMs, Contextual Word Embeddings and Data Augmentation—0
Image Captioning with Visual Object Representations Grounded in the Textual Modality—0
Impact of Gender Debiased Word Embeddings in Language Modeling—0
Impart Contextualization to Static Word Embeddings through Semantic Relations—0
Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network—0
Implicit Phenomena in Short-answer Scoring Data—0
Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings—0
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