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Sentence Embeddings

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Showing 251–275 of 615 papers

TitleStatusHype
Very Low Resource Sentence Alignment: Luhya and Swahili—0
Dial2vec: Self-Guided Contrastive Learning of Unsupervised Dialogue Embeddings—0
BERT-Flow-VAE: A Weakly-supervised Model for Multi-Label Text Classification—0
Pre-trained Sentence Embeddings for Implicit Discourse Relation Classification—0
Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning—0
Retrofitting Multilingual Sentence Embeddings with Abstract Meaning RepresentationCode0
Social Biases in Automatic Evaluation Metrics for NLG—0
Holistic Sentence Embeddings for Better Out-of-Distribution Detection—0
Unsupervised Sentence Textual Similarity with Compositional Phrase SemanticsCode0
GUSUM: Graph-based Unsupervised Summarization Using Sentence Features Scoring and Sentence-BERTCode0
Very Low Resource Sentence Alignment: Luhya and Swahili—0
Unsupervised Partial Sentence Matching for Cited Text Identification—0
CILex: An Investigation of Context Information for Lexical Substitution MethodsCode0
Incorporating the Rhetoric of Scientific Language into Sentence Embeddings using Phrase-guided Distant Supervision and Metric LearningCode0
Can Data Diversity Enhance Learning Generalization?—0
An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings LearningCode0
Text Complexity DE Challenge 2022 Submission Description: Pairwise Regression for Complexity Prediction—0
Generating Meaningful Topic Descriptions with Sentence Embeddings and LDA—0
Are Interaction Patterns Helpful for Task-Agnostic Dementia Detection? An Empirical Exploration—0
No means ‘No’; a non-im-proper modeling approach, with embedded speculative context—0
Building the Intent Landscape of Real-World Conversational Corpora with Extractive Question-Answering Transformers—0
Neural Embeddings for Text—0
Using Sentence Embeddings and Semantic Similarity for Seeking Consensus when Assessing Trustworthy AICode0
Fusing Sentence Embeddings Into LSTM-based Autoregressive Language ModelsCode0
Masked Autoencoders As The Unified Learners For Pre-Trained Sentence Representation—0
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