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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 2501–2550 of 4002 papers

TitleStatusHype
Inducing Bilingual Lexica From Non-Parallel Data With Earth Mover's Distance Regularization—0
Inducing Distant Supervision in Suggestion Mining through Part-of-Speech Embeddings—0
Inducing Embeddings for Rare and Unseen Words by Leveraging Lexical Resources—0
Inducing Relational Knowledge from BERT—0
INESC-ID: A Regression Model for Large Scale Twitter Sentiment Lexicon Induction—0
INESC-ID at SemEval-2016 Task 4-A: Reducing the Problem of Out-of-Embedding Words—0
INESC-ID: Sentiment Analysis without Hand-Coded Features or Linguistic Resources using Embedding Subspaces—0
InferLite: Simple Universal Sentence Representations from Natural Language Inference Data—0
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention—0
INF-HatEval at SemEval-2019 Task 5: Convolutional Neural Networks for Hate Speech Detection Against Women and Immigrants on Twitter—0
Information-Theory Interpretation of the Skip-Gram Negative-Sampling Objective Function—0
Word Equations: Inherently Interpretable Sparse Word Embeddingsthrough Sparse Coding—0
Initial Experiments in Data-Driven Morphological Analysis for Finnish—0
Injecting Wiktionary to improve token-level contextual representations using contrastive learning—0
Injecting Word Embeddings with Another Language's Resource : An Application of Bilingual Embeddings—0
Inline Detection of Domain Generation Algorithms with Context-Sensitive Word Embeddings—0
In Neural Machine Translation, What Does Transfer Learning Transfer?—0
Inspecting the concept knowledge graph encoded by modern language models—0
Instantiation—0
Integrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition—0
Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction—0
Integrating Lexical Knowledge in Word Embeddings using Sprinkling and Retrofitting—0
Integrating Pause Information with Word Embeddings in Language Models for Alzheimer's Disease Detection from Spontaneous Speech—0
Integrating Reviews into Personalized Ranking for Cold Start Recommendation—0
Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach—0
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs—0
Integration of Domain Knowledge using Medical Knowledge Graph Deep Learning for Cancer Phenotyping—0
Interactive Re-Fitting as a Technique for Improving Word Embeddings—0
Interdependencies of Gender and Race in Contextualized Word Embeddings—0
Interpretable Adversarial Training for Text—0
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts—0
Interpretable embeddings to understand computing careers—0
Interpretable Neural Embeddings with Sparse Self-Representation—0
Interpretable Word Embedding Contextualization—0
Interpretable Word Embeddings via Informative Priors—0
Interpreting Emoji with Emoji—0
Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings—0
Interpreting Word-Level Hidden State Behaviour of Character-Level LSTM Language Models—0
Inter-Sense: An Investigation of Sensory Blending in Fiction—0
Inter-Weighted Alignment Network for Sentence Pair Modeling—0
Intrinsic analysis for dual word embedding space models—0
Intrinsic Bias Metrics Do Not Correlate with Application Bias—0
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?—0
Intrinsic Image Captioning Evaluation—0
Introducing Syllable Tokenization for Low-resource Languages: A Case Study with Swahili—0
Invariance and identifiability issues for word embeddings—0
InvBERT: Reconstructing Text from Contextualized Word Embeddings by inverting the BERT pipeline—0
Investigating and Mitigating Stereotype-aware Unfairness in LLM-based Recommendations—0
Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings—0
Investigating Domain-Specific Information for Neural Coreference Resolution on Biomedical Texts—0
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